A method for evaluating the time for replacing a rolling cutter in a well drilling method

Abstract

The application provides a method for evaluating the time for replacing a rolling cutter in well drilling, comprising the following steps: step 1, calculating rock abrasivity based on the results of field geological exploration; step 2, analyzing the geometric parameters of the rock slag particles at the slag outlet; step 3, classifying the wear degree of the rolling cutter and establishing a wear index; step 4, quantifying the correlation between the rock slag parameters and the wear index of the rolling cutter; and step 5, using a fitting method to establish the relationship among the rock abrasivity, the geometric parameters of the rock slag particles and the wear index of the rolling cutter, and combining the threshold value set for the wear index of the rolling cutter to evaluate whether the rolling cutter needs to be replaced. The method can provide a beneficial reference for the decision of replacing the rolling cutter on site.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of drilling, in particular to a method for evaluating the replacement time of a cutter in shaft sinking by drilling. BACKGROUND

[0002] Coal is mostly located in Cretaceous-Jurassic weakly cemented strata, and deep and large vertical shafts are often constructed by artificial freezing method. Compared with the freezing method, shaft sinking by drilling has the advantages of high degree of mechanization, good construction environment, and excellent well completion quality. However, when drilling into the Jurassic strata, the cutter wears severely, and the drilling efficiency is low. Therefore, from the perspective of rock debris particle distribution characteristics and mineral composition, the study of the causes of cutter wear in shaft sinking by drilling is one of the important technical approaches to solving the problem of efficient rock breaking in shaft sinking by drilling.

[0003] Shaft sinking by drilling is a mechanical rock breaking and air lifting mud discharge construction process for vertical shafts, and its mechanical rock breaking working condition is quite different from that of TBM tunnel construction. At present, the research on rock breaking cutter wear mainly focuses on TBM tunnel construction, and there are few methods for quantifying cutter wear based on rock debris particle size characteristics and mineral composition.

[0004] The milling cutter is commonly used as the main rock breaking cutter in shaft sinking by drilling, and its working environment is filled with mud, pressure, and repeated impact load. Especially for the Jurassic and Cretaceous strata in the western region, some rock layers have high clay content, and the strata change complexly. The time and economic costs of pulling out the drill and replacing the cutter are very high, which has a great impact on the construction period and progress. There are many factors affecting the wear of the cutter in shaft sinking by drilling, such as rock strength, cutter material, mud properties, and drilling parameters. However, the technology of pulling out the drill and replacing the cutter in shaft sinking by drilling is still in the experience stage, and it has strong subjectivity and lacks certain data support to guide the replacement time of the drill and cutter. Generally, workers will choose to pull out the drill and replace the cutter when they observe that the drilling speed decreases significantly or the drilling pressure and torque fluctuate abnormally. However, this may be caused by strata change, which lacks scientific nature to some extent and easily leads to early or delayed replacement of the drill and cutter, seriously affecting the construction efficiency of shaft sinking by drilling. Rock debris, as an important feedback parameter, can reflect the drilling state during rock-mechanical interaction, and rock abrasion performance, as an important geological parameter, is obtained before drilling through geological drilling. Based on these two data and combined with the investigation of the wear state on site, the scientific problem of the blindness of the replacement time of the drill and cutter on site can be solved, so as to accurately predict the cutter wear of similar strata or similar methods. SUMMARY

[0005] The purpose of the present application is to provide a method for evaluating the replacement time of a cutter in shaft sinking by drilling, which can provide a useful reference for the decision-making of pulling out the drill and replacing the cutter on site.

[0006] In order to achieve the above-mentioned purpose, the present application provides the following technical solutions:

[0007] A method for evaluating the replacement timing of a cutting tool in a well drilling method, comprising the following steps:

[0008] Step 1, calculating the rock abrasivity based on the results of field geological exploration, Step 2, analyzing the geometric parameters of the slag particles at the slag outlet, Step 3, classifying the wear degree of the cutting tool and establishing a wear index, Step 4, quantifying the correlation between the slag particle parameters and the cutting tool wear index, Step 5, using a fitting method to establish the relationship between the rock abrasivity, the geometric parameters of the slag particles and the cutting tool wear index, and combining the threshold value set for the cutting tool wear index to evaluate whether to replace the cutting tool.

[0009] Further, in the above-mentioned method for evaluating the replacement timing of a cutting tool in a well drilling method, in the step 1, the rock abrasivity is calculated by the following method:

[0010] The equivalent quartz content EQC is calculated by thin section analysis:

[0011]

[0012] In formula (1), V i is the mass percentage of the i-th mineral in the rock, %; R i is the ratio of the hardness of the i-th mineral to that of quartz; m is the number of mineral types,

[0013] The rock abrasivity index RAI is obtained in combination with the uniaxial compressive strength of the rock as follows:

[0014] RAI = EQC·UCS (2)

[0015] In formula (2), UCS is the uniaxial compressive strength of the rock, MPa.

[0016] Further, in the above-mentioned method for evaluating the replacement timing of a cutting tool in a well drilling method, in the step 2, specifically comprising:

[0017] The rock slag particle is wrapped by gradually reducing ellipses until the ellipse circumscribes the rock slag particle, and a fitting ellipse is obtained. The major axis and the minor axis of the fitting ellipse are measured as L1 and L2, respectively, and the rock slag ellipticity parameter E p As shown in formula (3),

[0018]

[0019] The same circle as the particle area S is constructed and identified using a fitting method, and an equivalent circle of the particle is obtained. The equivalent circle diameter R is calculated by formula (4), and therefore the particle area S and the equivalent circle diameter R can be used to evaluate the particle size,

[0020]

[0021] The circularity Ci The definition formula is shown as formula (5), C i The value is closer to 1, the closer the particle is to a circle, and conversely C i The value is closer to 0, the more elongated the particle is, and C in formula (5) is the perimeter of the particle,

[0022]

[0023] In order to characterize the size distribution of the rock slag particles, the equivalent circle diameter of the particles is taken as the screening object, and an exponential function similar to the exponential function with the natural constant e as the base number is constructed as the distribution function to describe the particle size distribution of the rock slag, and the function expression is:

[0024]

[0025] In formula (6): is the cumulative passing rate, %; is the equivalent circle diameter of the particle, cm; P1 is the maximum cumulative passing rate, D t is the minimum particle size of the particle, and in the same group of rock slag identification data, both are fixed values, in order to obtain a better fitting effect, both are set as one of the fitting parameters; define k / B t UC is the uniformity coefficient of the rock slag particle, and the smaller the value of UC indicates that the size distribution of the rock slag is more uniform.

[0026] Further, in the drill method shaft sinking cutter replacement timing evaluation method, in step 3, the cutter wear degree is divided into 5 levels, which are slight wear w1, general wear w2, moderate wear w3, severe wear w4 and complete failure w5.

[0027] Further, in the drill method shaft sinking cutter replacement timing evaluation method, in step 3, the cutter surface wear-resistant welding layer is not worn out, the rolling wear is 0-5mm, and the cutter shaft state is checked on site, which is defined as slight wear w1 and can continue to be used,

[0028] The inclined friction wear of the cutter surface wear-resistant welding layer is worn out, and according to the wear length, the wear degree is defined as w2, w3 and w4 respectively in the intervals of 5mm-10mm, 10mm-15mm and 15mm-20mm,

[0029] The irregular wear and the flat friction wear form a wear step at the top of the cutter tooth, and according to the wear length, the wear degree is defined as w2, w3 and w4 respectively in the intervals of 5mm-10mm, 10mm-15mm and 15mm-20mm,

[0030] According to the wear slope length of the side cutter and the cutter holder in the intervals of 0-5mm, 5mm-10mm, 10mm-15mm and 15mm-20mm, the wear degrees are defined as w1, w2, w3 and w4 respectively,

[0031] Tooth breakage and shell breaking belong to structural damage of the cutter and are defined as complete failure, and the wear degree is defined as w5.

[0032] Further, in the drilling method well sinking cutter replacement timing evaluation method, in step 3, the single cutter average wear index As shown in formula (7),

[0033]

[0034] In the formula, n is the number of cutters installed on the cutter head, and

[0035] The standard deviation of the single cutter average wear index is taken as the wear uniformity index σ w , and the expression is shown in formula (8),

[0036]

[0037] The single cutter average wear index The wear uniformity index σ w is taken as the cutter wear prediction basis.

[0038] Further, in the drilling method well sinking cutter replacement timing evaluation method, in step 4, the Pearson coefficient is used to quantify the correlation between the rock slag parameters and the cutter wear index, and the Pearson coefficient calculation formula is as follows:

[0039]

[0040] In formula (9), r is the Pearson coefficient; X i and Y i are the values of the two variables respectively; are the mean values of the two variables respectively,

[0041] The correlation between the rock slag geometric parameters and the cutter wear correlation index is in the order of rock slag particle size distribution>roundness parameter>uniformity coefficient>ellipticity parameter,

[0042] Among them, the correlation between the rock slag large particle proportion POP, the roundness box width BW and the single cutter average wear index w is relatively high, and the correlation between the uniformity coefficient UC and the wear uniformity index σ w is the highest,

[0043] Therefore, for the rock slag geometric parameters, the rock slag large particle proportion POP, the roundness box width BW and the uniformity coefficient UC are selected as the three fitting independent variables of the wear prediction model.

[0044] Furthermore, in the above-mentioned method for assessing the timing of cutting tool replacement during well drilling, in step 4,

[0045] The correlation between rock abrasiveness-related indices and cutter wear-related indices is as follows: RAI > UCS > Quartz content > EQC > Feldspar content.

[0046] For rock abrasiveness-related indices, RAI was selected as a fitting independent variable for the wear prediction model.

[0047] The box width (BW) for rock slag roundness distribution, the proportion of large particles (POP), the uniformity coefficient (UC), and the rock abrasion index (RAI) were selected as independent variables, and the average wear index of a single cutter was used as the criterion. Wear uniformity index σ w Using the variable as the dependent variable, perform multivariate nonlinear regression.

[0048] Furthermore, in the above-mentioned method for assessing the timing of cutting tool replacement during well drilling, in step 5,

[0049] The regression results for different rock strata are shown below:

[0050] Sandy rock strata:

[0051]

[0052] Muddy rock strata:

[0053]

[0054] In formulas (10)-(13): α and β are the average wear indices of a single tool. Wear uniformity index σ w The fit index, R 2 R represents the goodness of fit of the function. 2 The larger the value, the higher the fitting accuracy.

[0055] Furthermore, in the above-mentioned method for assessing the timing of cutting tool replacement during well drilling, in step 5,

[0056] Based on the on-site tool change records, when the average wear index of a single tool... Or wear uniformity index σ w When the value is ≥1, the tool needs to be replaced;

[0057] When the average wear index of a single tool And the wear uniformity index σ w When the value is less than 1, there is no need to change the tool.

[0058] Analysis shows that the present invention discloses a method for evaluating the timing of replacing the cutting roller in drilling, which calculates the rock abrasiveness based on the results of on-site geological exploration; during drilling, rock debris is retrieved and processed, and the geometric parameters of the rock debris are obtained by combining image recognition methods; the parameters are substituted into equations (12) to (15) to obtain the average wear index and wear uniformity index of a single cutter, and the cutting roller is replaced according to the aforementioned evaluation criteria. Attached Figure Description

[0059] The accompanying drawings, which form part of this application, are used to provide a further understanding of the invention. The illustrative embodiments of the invention and their descriptions are used to explain the invention and do not constitute an undue limitation of the invention. Wherein:

[0060] Figure 1 This is a schematic diagram showing the shape parameters of the rock slag particles at the slag outlet.

[0061] Figure 2 This is a schematic diagram showing the distribution of roundness and ellipticity of rock debris in a weakly cemented sandy stratum.

[0062] Figure 3 This is a schematic diagram showing the distribution of roundness and ellipticity of rock debris within a clayey cemented stratum.

[0063] Figure 4 This is a schematic diagram showing the distribution of roundness and ellipticity of rock debris within calcareous cemented mud and sand interbedded strata.

[0064] Figure 5 This is a schematic diagram showing the distribution of roundness and ellipticity of rock debris within calcareous and ferruginous cemented sandy strata.

[0065] Figure 6 This is a schematic diagram illustrating the cumulative distribution of rock debris particle size in a weakly cemented sandy stratum.

[0066] Figure 7 This is a schematic diagram illustrating the cumulative distribution of rock debris particle size within argillaceous cemented strata.

[0067] Figure 8 This is a schematic diagram illustrating the cumulative distribution of rock debris particle size within calcareous cemented mud and sand interbedded strata.

[0068] Figure 9 This is a schematic diagram illustrating the cumulative distribution of rock debris particle size within calcareous and ferruginous cemented sandy strata.

[0069] Figure 10 This is a schematic diagram of cutterhead wear in a weakly cemented sandy formation.

[0070] Figure 11 This is a schematic diagram of cutterhead wear in a clayey cemented muddy stratum.

[0071] Figure 12This is a schematic diagram of cutterhead wear in a formation consisting of calcareous cemented mud and interbedded sand.

[0072] Figure 13 This is a schematic diagram of cutterhead wear in a calcareous and ferrous cemented sandy formation.

[0073] Figure 14 This is a schematic diagram of the cutter head hob layout.

[0074] Figure 15 This is a heatmap showing the correlation between the geometric parameters of rock slag and the wear-related indicators of the cutter roller.

[0075] Figure 16 A heatmap showing the correlation between parameters related to the abrasiveness of rock slag and indices related to cutter wear.

[0076] Figure 17 A comparison chart of wear prediction model calculations and field-measured cutter wear values ​​in weakly cemented sandy formations.

[0077] Figure 18 Comparison chart of wear prediction model values ​​and measured values ​​of cutter wear in argillaceous cemented formations.

[0078] Figure 19 Comparison chart of wear prediction model values ​​and measured values ​​of cutter wear in calcareous cemented mud and sand interbedded strata.

[0079] Figure 20 A comparison chart of wear prediction model values ​​and measured values ​​of cutter wear in calcareous and ferrous cemented sandy strata.

[0080] Figure 21 This is a schematic diagram of a drilling method for evaluating the timing of cutting tool replacement in well sinking, according to an embodiment of the present invention. Detailed Implementation

[0081] The present invention will now be described in detail with reference to the accompanying drawings and embodiments. Various examples are provided by way of explanation and not by way of limitation. Indeed, those skilled in the art will recognize that modifications and variations can be made to the invention without departing from its scope or spirit. For example, a feature shown or described as part of one embodiment may be used in another embodiment to produce yet another embodiment. Therefore, it is desirable that the invention encompass such modifications and variations falling within the scope of the appended claims and their equivalents.

[0082] The accompanying drawings illustrate one or more examples of the invention. The detailed description uses numbers and letters to refer to features in the drawings. Similar or analogous reference numerals in the drawings and description have been used to refer to similar or analogous parts of the invention.

[0083] likeFigures 1 to 21 As shown in the embodiment of the present invention, a method for assessing the timing of cutting tool replacement in drilling well sinking is provided, comprising the following steps:

[0084] Step 1: Calculate rock abrasiveness based on on-site geological exploration results

[0085] Rock abrasiveness is calculated using the following method:

[0086] (1) Calculation of equivalent quartz content (EQC) through thin section analysis:

[0087]

[0088] In formula (1): V i R represents the mass percentage of the i-th mineral in the rock, in %; i denoted as the ratio of the Rockwell hardness of the i-th mineral to that of quartz; m represents the mineral type.

[0089] (2) The rock abrasion index RAI is obtained by combining the uniaxial compressive strength of the rock:

[0090] RAI = EQC·UCS (2)

[0091] In formula (2): UCS is the uniaxial compressive strength of rock, MPa.

[0092] For the aforementioned well drilling project, field and laboratory tests were conducted on the 11 drilling sections, including drilling, coring, thin section analysis, and uniaxial compressive strength testing. The abrasiveness indices of different formations are shown in Table 1. Based on the naming of the main rocks inhabiting the strata in Table 1, the different drilling sections can be divided into four types of formations: very weakly cemented sandy strata, argillaceous cemented argillaceous strata, calcareous cemented argillaceous / sand interbedded strata, and ferruginous cemented sandy strata, encompassing the 11 drilling sections.

[0093] Weakly cemented sandy strata and ferruginous cemented sandy strata are collectively referred to as sandy strata.

[0094] Cemented muddy strata and calcareous cemented mud and sand interbedded strata are collectively referred to as muddy strata.

[0095] Table 1. Relevant Indicators of Rock Abrasiveness

[0096]

[0097] Step 2: Analyze the geometric parameters of the slag particles at the slag mouth.

[0098] Before changing the drill bit, a net is used to collect rock debris at the slag outlet. After drying, washing, and re-drying, rock particles are obtained, and the source image files are photographed and saved. Image processing software is used to identify the shape parameters of the particles, such as area, major and minor axes, and roundness, and the geometric morphology and particle distribution patterns of the rock debris are statistically analyzed.

[0099] A schematic diagram of the shape parameters of rock slag particles at the slag outlet is shown below. Figure 1 As shown.

[0100] Since the particle size of rock debris ranges from 0.01 to 10 cm, a regular camera can meet the identification requirements.

[0101] (1) By gradually shrinking the ellipse around the rock debris particles until the ellipse is circumscribed by the rock debris particles, the following is obtained: Figure 2 The fitted ellipse shown is obtained by measuring its major and minor axes as L1 and L2, respectively, and then obtaining the ellipticity parameter E of the rock slag. p As shown in formula (3).

[0102]

[0103] (2) Use the fitting method to construct a circle with the same area S as the identified particle to obtain the particle equivalent circle. Calculate the equivalent circle diameter R using formula (4). Therefore, the particle area S and the equivalent circle diameter R can be used to evaluate the particle size.

[0104]

[0105] (3) Roundness C i The definition is shown in formula (5), C i The closer the value is to 1, the closer the particle is to a spherical shape; conversely, C... i The closer the value is to 0, the finer and longer the particles are. In formula (5), C is the particle circumference.

[0106]

[0107] Based on the above method, the statistical characteristics of rock debris are analyzed by examining the shape and size distribution of the rock debris particles. Roundness and ellipticity are used to describe the shape of the rock debris particles, while area is used to filter particles and perform cumulative statistics to describe the particle size distribution.

[0108] The statistical characteristics of 11 groups of rock debris particle shapes were obtained by plotting roundness as the x-axis and ellipticity as the y-axis. Figures 2-5 As shown in the box plot. The box width represents the difference between the upper and lower quartiles. The blue dots inside the box represent the mean, the blue line represents the median, and the red dots outside the upper and lower limits represent outliers.

[0109] according to Figure 1 Using area as the screening target, 0–0.01 cm 2 Small particles, 0.01–1 cm 2 Medium-sized particles, 1–10 cm 2 The rock slag particles are large, and the cumulative distribution pattern of particle size is shown in Table 2. Figures 6-9 As shown.

[0110] Table 2. Cumulative Distribution Pattern of Rock Slag Particle Size / %

[0111]

[0112] To characterize the size distribution of rock slag particles, the equivalent circular diameter of the particles was used as the screening factor. The cumulative characteristic identification curve was fitted to the distribution function, and the result was obtained through R... 2 To determine whether a certain distribution model is satisfied, an exponential-like function with the natural constant e as the base is constructed as the distribution function to describe the particle size distribution of the rock slag. The function expression is as follows:

[0113]

[0114] In formula (6): Cumulative pass rate, %; D is the equivalent circle diameter of the particle, in cm; P1 is the maximum cumulative throughput, in cm. t For the minimum particle size, both k / B and k are constant values ​​in the same set of rock slag identification data. To obtain a better fitting effect, k / B is set as one of the fitting parameters. t is the uniformity coefficient (UC) of rock debris particles; the smaller the value, the more uniform the size distribution of the rock debris.

[0115] The main fitting parameters for rock slag accumulation are shown in Table 3.

[0116] Table 3. Main fitting parameters for rock slag accumulation

[0117]

[0118] Step 3: Classify the degree of hob wear and establish wear indexes.

[0119] Based on the hob wear failure mode, the degree of hob wear is divided into 5 levels, namely slight wear w1, general wear w2, moderate wear w3, severe wear w4, and complete failure w5.

[0120] The wear-resistant weld layer on the surface of the hob is not completely worn away during rolling wear, and the wear slope is 0-5mm. Based on the on-site inspection of the cutter shaft condition, it is defined as slight wear w1, and it can continue to be used.

[0121] The inclined friction wear of the hob surface where the wear-resistant weld layer is almost completely worn away is defined as w2, w3, and w4 according to the wear slope length in three ranges: 5mm~10mm, 10mm~15mm, and 15mm~20mm, respectively.

[0122] Irregular wear and planar friction wear form wear steps at the tip of the cutting teeth. Based on the wear slope length, which is in three ranges of 5mm~10mm, 10mm~15mm, and 15mm~20mm respectively, the degree of wear is defined as w2, w3, and w4 respectively.

[0123] Based on the wear slope lengths of the edge cutter and the cutter holder being in four ranges—0–5 mm, 5 mm–10 mm, 10 mm–15 mm, and 15 mm–20 mm—the wear degree is defined as w1, w2, w3, and w4, respectively.

[0124] Tooth breakage and delamination are structural damages to hobs and are defined as complete failures, with the wear level defined as w5.

[0125] Based on the above-mentioned wear characteristics of the hob, the hob wear degree evaluation matrix is ​​shown in Table 4.

[0126] Table 4 Evaluation Matrix of On-Site Hob Wear Degree

[0127]

[0128]

[0129] To visualize the relationship between hob wear and its position on the cutter head, a hob wear heat map was drawn based on Table 4 and field survey data, as shown below. Figures 10-13 As shown.

[0130] Average wear index of a single tool As shown in formula (7).

[0131]

[0132] In the formula: n is the number of hobs installed on the cutter head.

[0133] In drilling operations, the deep wear zone of the cutterhead tends to concentrate in cutter rings b, c, and d, while the central cutter and its surrounding area are mostly shallow wear zones. In very weakly cemented sandy formations and argillaceous cemented muddy formations, cutterhead wear is generally centrally symmetrical. However, in calcareous cemented muddy and sandy interbedded formations, and calcareous and ferruginous cemented sandy formations, the cutterhead wear is non-centrally symmetrical and uneven.

[0134] Explanation of cutter rings b, c, and d: The edge cutter is ring a, the center cutter is k, and b through j are the main cutters. From the edge cutter to the center cutter, each cutter ring has 6, 3, 3, 2, 2, 2, 2, 2, 2, 1, and 1 cutters respectively. The hobbing cutters within the same cutter ring have the same installation radius, and the rock-breaking range of the hobbing cutters in adjacent cutter rings has a certain degree of overlap. For example... Figure 14 As shown.

[0135] Replacing cutter rollers in well drilling involves multiple processes, including hoisting the drill string, evaluating wear, disassembling and reassembling the rollers, and running the drill string back down. To reduce auxiliary drilling time, improve drilling efficiency, and lower costs, the field tends to replace all rollers each time the drill string is hoisted. Therefore, before hoisting the drill string for cutter replacement, a roller wear uniformity evaluation is conducted to determine the appropriate time to hoist the drill string and reduce the number of hoisting operations. Thus, the standard deviation of the average wear index of a single cutter is used as the wear uniformity index σ.w The expression is shown in formula (8).

[0136]

[0137] According to formulas (7) and (8), the average wear index of a single blade can be obtained. Wear uniformity index σ w The calculated values ​​are shown in Table 5. σ w The process quantity that reflects the wear state of the cutter head hob during drilling can be used as a basis for predicting hob wear.

[0138] Table 5 Calculation values ​​of wear index

[0139]

[0140] Step 4: Quantify the correlation between rock slag parameters and cutter wear index.

[0141] The Pearson coefficient was used to quantify the correlation between rock slag parameters and cutter wear indices. The formula for calculating the Pearson coefficient is as follows:

[0142]

[0143] In formula (9): r is the Pearson coefficient; X i Y i These are the values ​​of the two variables; These are the means of the two variables, respectively.

[0144] Based on 11 sets of drilling data, a heatmap showing the correlation between rock cuttings geometric parameters and cutter wear indices was plotted, as shown below. Figure 15 As shown, Region I represents the autocorrelation of the geometric parameters of rock slag, while Region II represents the correlation between the geometric parameters of rock slag and the wear-related indicators of the cutter.

[0145] Depend on Figure 15 It can be seen that the correlation between the geometric parameters of rock slag and the wear-related indicators of the cutter is as follows: rock slag particle size distribution > roundness parameter > uniformity coefficient > ellipticity parameter. Among them, the proportion of large rock slag particles (POP), the roundness box width (BW), and the average wear index of a single cutter are the most relevant. The correlation between the uniformity coefficient UC and the wear uniformity index σ is relatively high. w The correlation was the highest. Therefore, for the geometric parameters of rock slag, the proportion of large rock slag particles (POP), the roundness box width (BW), and the uniformity coefficient (UC) were selected as the three fitting variables for the wear prediction model.

[0146] Table 1 shows the relevant indices of rock abrasiveness. Based on the above, a heatmap showing the correlation between rock cuttings geometric parameters and cutter wear indices is drawn as follows: Figure 15As shown in the figure, regions I and III represent the autocorrelation between rock abrasion-related parameters and cutter wear-related indices, while region II represents the correlation between rock abrasion-related parameters and cutter wear-related indices.

[0147] Depend on Figure 16 It can be seen that the correlation between rock abrasiveness-related indices and cutter wear-related indices is as follows: RAI > UCS > Quartz content > EQC > Feldspar content. Therefore, for rock abrasiveness-related indices, RAI is selected as a fitting independent variable for the wear prediction model.

[0148] In summary, the box width (BW), large particle proportion (POP), uniformity coefficient (UC), and rock abrasion index (RAI) of rock slag roundness distribution were selected as independent variables, and the average wear index of a single cutter was used as the criterion. Wear uniformity index σ w Using the variable as the dependent variable, perform multivariate nonlinear regression.

[0149] Step 5: Use a fitting method to establish the relationship between rock abrasiveness, rock slag particle geometric parameters and cutter wear index, and evaluate whether to replace the cutter based on the threshold set for the cutter wear index.

[0150] The regression results for different rock strata are shown below:

[0151] Sandy rock strata:

[0152]

[0153] Muddy rock strata:

[0154]

[0155] In formulas (10)-(13): α and β are the average wear indices of a single tool. Wear uniformity index σ w The fit index, R 2 R represents the goodness of fit of the function. 2 The larger the value, the higher the fitting accuracy.

[0156] When the average wear index of a single cutter is too high, the rock-breaking efficiency of the cutterhead decreases, which in turn reduces the drilling speed. When the wear uniformity of the cutterhead is poor, it is easy to cause excessive eccentric torque of the cutterhead, which will cause the drilling pressure and torque fluctuation to increase, thereby aggravating the wear and failure of the cutterhead.

[0157] Based on the on-site tool change records, when the "average wear index of a single tool" Or wear uniformity index σ w When the value is ≥1", the cutter head hob is no longer suitable for continued drilling and needs to be replaced.

[0158] When "single-blade average wear index" And the wear uniformity index σ w When <1", there is no need to change the tool.

[0159] like Figures 17-20 This is a comparison chart showing the relationship between the predicted model's calculated values ​​and the actual measured values ​​of cutter wear from on-site surveys. Data points falling into area (a) indicate that cutter replacement is not required, while area (b) indicates that cutter replacement is necessary. For the average wear index per cutter, 9 points fall into area (b), 1 point into area (a), and only 1 point into area (c). For the wear uniformity index, 6 points are in area (b), 4 points are in area (a), and 1 point is in area (c). Combining these two indicators to determine whether to replace the drill bit shows only one misjudgment across 11 drilling sections, achieving a 90.9% success rate in predicting whether to lift the drill bit and replace the cutter.

[0160] Propose such as Figure 21 The method for evaluating the timing of cutting tool replacement in well drilling is as follows: the rock abrasiveness is calculated based on the results of on-site geological exploration; during drilling, rock debris is retrieved and processed, and the geometric parameters of the rock debris are obtained by combining image recognition methods; the parameters are substituted into equations (12) to (15) to obtain the average wear index and wear uniformity index of a single tool, and the cutting tool is replaced according to the aforementioned evaluation criteria.

[0161] As can be seen from the above description, the embodiments of the present invention achieve the following technical effects:

[0162] (1) The wear of drilling cutter rollers is closely related to the geological conditions of the rock strata. The cutter rollers consumed per unit footage in different strata are as follows: muddy cemented muddy strata > calcareous cemented mud and sand interbedded strata ≈ calcareous and ferruginous cemented sandy strata > very weakly cemented sandy strata.

[0163] (2) The statistical characteristics of the geometric morphology of rock debris can indirectly reflect the degree of wear of the cutter per unit advance in different strata. The particle size distribution of rock debris in the Cretaceous and Jurassic strata conforms to an exponential function, with a correlation coefficient R2 of 0.976 to 0.997. The uniformity coefficient can be used to describe the uniformity of rock debris and has a high correlation with the uniformity index of cutter wear.

[0164] (3) Using the width of the rock slag roundness distribution box, the proportion of large particles, the uniformity coefficient, and the rock abrasiveness index as the main factors of cutter wear, a cutter wear prediction model applicable to Cretaceous and Jurassic strata was fitted. Compared with the field measured indicators, the model prediction success rate reached 90.9%.

[0165] (4) The proposed hob wear assessment method has good operability. Specifically, when the average wear index of a single hob... Or wear uniformity index (σ) w When the value is greater than or equal to 1, it indicates that the cutterhead hob is no longer suitable for continued drilling. This criterion can provide a useful reference for on-site decisions regarding drill bit removal and cutter replacement.

[0166] The above description is merely a preferred embodiment of the present invention and is not intended to limit the invention. Various modifications and variations can be made to the present invention by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. A method for assessing the timing of cutting tool replacement in well drilling, characterized in that, Includes the following steps: Step 1: Calculate rock abrasiveness based on on-site geological exploration results. Step 2: Analyze the geometric parameters of the slag particles at the slag outlet. Step 2 specifically includes: By gradually shrinking the ellipse particles and wrapping them with an ellipse until the ellipse is circumscribed by the particles, a fitted ellipse is obtained. The major and minor axes of the fitted ellipse are measured as L1 and L2, respectively, and the ellipticity parameter E of the rock debris is obtained accordingly. p As shown in formula (3), A circle with the same area S as the identified particle is constructed using a fitting method to obtain the particle's equivalent circle. The diameter R of the equivalent circle is then calculated using formula (4). The particle area S and the equivalent circle diameter R can be used to evaluate the particle size. Roundness C i The definition is shown in formula (5), C i The closer the value is to 1, the closer the particle is to a spherical shape; conversely, C... i The closer the value is to 0, the finer and longer the particles are. In formula (5), C is the particle circumference. To characterize the size distribution of rock slag particles, the equivalent circular diameter of the particles is used as the selection factor. A quasi-exponential function with the natural constant e as the base is constructed as the distribution function to describe the particle size distribution of rock slag. The function expression is as follows: In formula (6): Cumulative pass rate; D is the equivalent circle diameter of the particle, in cm; P1 is the maximum cumulative throughput, and D... t For the minimum particle size, both k / B and k are constant values ​​in the same set of rock slag identification data. To obtain a better fitting effect, k / B is set as one of the fitting parameters. t UC represents the uniformity coefficient of rock fragment particles. The smaller the UC value, the more uniform the size distribution of the rock fragment. Step 3: Classify the degree of hob wear and establish wear indicators. Step 4: Quantify the correlation between rock slag parameters and cutter wear index. Step 5: Use a fitting method to establish the relationship between rock abrasiveness, rock debris particle geometry parameters, and cutter wear index. Combine this with a threshold set for the cutter wear index to evaluate whether to replace the cutter. For rock abrasiveness-related indices, the Rock Abrasiveness Index (RAI) was selected as a fitting independent variable for the wear prediction model. The box width (BW) for rock slag roundness distribution, the proportion of large particles (POP), the uniformity coefficient (UC), and the rock abrasion index (RAI) were selected as independent variables, and the average wear index of a single cutter was used as the criterion. Wear uniformity index σ w Using the variable as the dependent variable, perform multivariate nonlinear regression.

2. The method for assessing the timing of cutting tool replacement in well drilling according to claim 1, characterized in that, In step 1, the rock abrasiveness is calculated using the following method: Equivalent Quartz Content (EQC) was calculated using thin-section analysis. In formula (1): V i R represents the mass percentage of the i-th mineral in the rock; i denoted as the ratio of the Rockwell hardness of the i-th mineral to that of quartz; m represents the mineral type. The rock abrasion index RAI, obtained by combining the uniaxial compressive strength of the rock, is: RAI = EQC·UCS (2) In formula (2): UCS is the uniaxial compressive strength of rock, in MPa.

3. The method for assessing the timing of cutting tool replacement in well drilling according to claim 1, characterized in that, In step 3, the wear degree of the hob is divided into 5 levels, namely slight wear w1, moderate wear w2, medium wear w3, severe wear w4, and complete failure w5.

4. The method for assessing the timing of cutting tool replacement in well drilling according to claim 3, characterized in that, In step 3, the rolling wear of the hob surface where the wear-resistant weld layer has not been completely worn away, with a wear slope of (0, 5 mm], is defined as slight wear w1 by on-site inspection of the cutter shaft condition, and it can continue to be used. The inclined frictional wear of the hob surface, where the wear-resistant weld layer is almost completely worn away, is defined as w2, w3, and w4 respectively, based on the wear slope length falling within three intervals: (5mm, 10mm], (10mm, 15mm], and (15mm, 20mm]. Irregular wear and planar friction wear form wear steps at the tip of the cutting teeth. Based on the wear slope length, these steps fall within three intervals: (5mm, 10mm], (10mm, 15mm], and (15mm, 20mm]. The wear degree is defined as w2, w3, and w4, respectively. Based on the wear slope lengths of the edge tool and tool holder falling within four intervals: (0, 5 mm], (5 mm, 10 mm], (10 mm, 15 mm], and (15 mm, 20 mm], the wear degree is defined as w1, w2, w3, and w4, respectively. Tooth breakage and delamination are structural damages to hobs and are defined as complete failures, with the wear level defined as w5.

5. The method for assessing the timing of cutting tool replacement in well drilling according to claim 4, characterized in that, In step 3, the average wear index of a single tool As shown in formula (7), In the formula: n is the number of hobs installed on the cutter head. The standard deviation of the average wear index of a single tool is used as the wear uniformity index σ. w The expression is shown in formula (8). Average wear index of a single tool Wear uniformity index σ w As a basis for predicting hob wear.

6. The method for assessing the timing of cutting tool replacement in well drilling according to claim 5, characterized in that, In step 4, the Pearson coefficient is used to quantify the correlation between rock slag parameters and cutter wear index. The formula for calculating the Pearson coefficient is as follows: In formula (9): r is the Pearson coefficient; X i Y i These are the values ​​of the two variables; These are the means of the two variables, respectively. The correlation between the geometric parameters of rock slag and the related indicators of cutter wear is as follows: correlation between rock slag particle size distribution and the related indicators of cutter wear > correlation between roundness parameter and the related indicators of cutter wear > correlation between uniformity coefficient and the related indicators of cutter wear > correlation between ellipticity parameter and the related indicators of cutter wear. Among them, the proportion of large rock debris particles (POP), the roundness box width (BW), and the average wear index of a single cutter are... The correlation between the uniformity coefficient UC and the wear uniformity index σ is relatively high. w The correlation was the highest. For the geometric parameters of rock slag, the proportion of large rock slag particles (POP), the roundness box width (BW), and the uniformity coefficient (UC) were selected as the three fitting variables for the wear prediction model.

7. The method for assessing the timing of cutting tool replacement in well drilling according to claim 6, characterized in that, In step 4, The correlations between rock abrasiveness-related indices and cutter wear-related indices are as follows: RAI > UCS > quartz content > EQC > feldspar content.

8. The method for assessing the timing of cutting tool replacement in well drilling according to claim 5, characterized in that, In step 5, The regression results for different rock strata are shown below: Sandy rock strata: Muddy rock strata: In formulas (10)-(13): α and β are the average wear indices of a single tool. Wear uniformity index σ w The fit index, R 2 R represents the goodness of fit of the function. 2 The larger the value, the higher the fitting accuracy.

9. The method for assessing the timing of cutting tool replacement in well drilling according to claim 5, characterized in that, In step 5, Based on the on-site tool change records, when the average wear index of a single tool... Or wear uniformity index σ w When the value is ≥1, the tool needs to be replaced; When the average wear index of a single tool And the wear uniformity index σ w When the value is less than 1, there is no need to change the tool.

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