This study is aimed at detecting small faults in coal seams. With coal seams of different buried depths in Luling Coal Mine, Yuenan Coal Mine, and Sihe Coal Mine with obvious difference in hardness and outburst hazards selected as the research objects, the morphological characteristics of a sample particle size such as the Rosin-Rammler distribution function, average particle size, cumulative mass distribution, and mechanical parameters such as particle strength and value were statistically analyzed through drill cuttings related to sampling points at different positions of faults already known. The results show that the effect of tectonic stress reduces the strength and permeability of the coal after the borehole enters the fault damage zone, resulting in abnormal fluctuations in the morphological characteristics of the drill cuttings. Correspondingly, large-size particles account for a high percentage. The weight analysis discloses that the characteristic particle size of the Rosin-Rammler distribution function has the greatest influence on the determination of fault existence. The analysis of drill cutting characteristics conduces to detecting the distribution of small faults, helps to improve the utilization of mine information, and is of great significance for accident prevention and control.

1. Introduction

Many structures are formed in coal seams during the long geological and tectonic evolution [1]. Among them, the most common is faults whose sizes range from hundreds of kilometers (along the strike) to a few tens of centimeters. Faults seriously damage the continuity and integrity of the rock and lead to the formation of tectonic coal and the abnormal distribution of stratigraphic stress [24]. Consequently, the production plan of coal mining enterprises is disrupted, and the vicinity of the fault becomes a dangerous area prone to dynamic disasters such as coal and gas outburst [5]. However, traditional detection methods can hardly obtain complete geological information on coal seams, especially for faults with a fall less than 5 m [6]. Failure to achieve accurate detection results in great safety risks in the production process. Since the first recorded outburst accident in 1834, more than 40,000 outburst accidents have been reported worldwide, of which nearly half occurred in China [7, 8]. Nowadays, with the growth of energy demand and resource depletion, coal production is moving towards deeper strata. At present, 80% of the coal mining work reaches over 800 m. Accordingly, outburst hazards are on the rise year by year [9, 10]. Relevant data show that the outburst accidents in Chinese mines are closely related to the geological structure. Among the 150 outburst accidents in Pingdingshan Mining Area, North China’s Henan Province, 118 were related to the geological structure. Besides, 71.8% of the outburst accidents in crosscut and coal roadway in Huainan Mining Area, Central China’s Anhui Province, occurred in the vicinity of small faults [11]. Due to the complexity and variability of outburst accidents, many factors are involved, and different factors account for different outburst accidents. Usually, scholars study this problem from the following aspects. (1)Most outburst accidents are concentrated in the stress concentration area susceptible to mining disturbance, and stress is the power and energy source to cause coal rock failure in the outburst process. Therefore, it is particularly important to clarify the stress distribution of strata. During the simulation experiment of outburst process in gas-rich area, Tu found that the stress was the dominant factor inducing the prestripping failure of outburst coal in the outburst development stage [12]. The stress causing outbursts includes original rock stress and disturbance stress. Disturbance stress includes both additional stress generated by mining activities and concentrated stress generated by stress transfer due to activities which break the equilibrium state of the original rock stress(2)The permeability of coal directly controls the gas flow in the pore and fracture system [1315]. Under the action of tectonic stress, the pore and fracture structure in the coal body changes and further changes the gas seepage characteristics of the coal seam in the region, resulting in the uneven distribution of gas and the formation of local gas enrichment areas, which provides capacity conditions for the breeding of outburst(3)As another power source of outburst accidents, gas is also an important factor involved in outburst accidents. On the one hand, the weakening effect of gas in pores and fractures on coal makes coal prone to damage and failure [16]. On the other hand, the rapid desorption of gas provides much transportation power for coal rock during accidents, which is also a prerequisite for the continuous development of accidents [17](4)As the main carrier of outburst accidents, coal is the main carrier of outburst accidents, and all outburst energy acts on it. Therefore, theoretically and experimentally, researches are carried out on the correlation between the energy consumption of coal crushing and its physical properties during outburst. For example, Luo et al. [18] analyzed the relationship between energy input and new surface area of particles by the drop hammer experiment. Then, they distinguished the geometric characteristics of fine particles of outburst and nonoutburst coals and evaluated the energy dissipation of broken coal during coal and gas outburst. Wang et al. [19] tested the size distribution of coal particles under static loading and dynamic impact test and proposed a mathematical model for calculating the surface energy of coal. Although such researches were carried out in isolation from the actual occurrence conditions, they quantified the energy relations and crushing effect during coal crushing, which provided more reference for studying the mechanism of outburst accidents

Based on the above researches, many scholars proposed mathematical prediction methods and direct monitoring methods for the prevention of outburst accidents. The mathematical prediction methods use fuzzy mathematics, cluster analysis, artificial neural network, etc. to predict outburst accidents [2026]. The direct prediction methods are based on physical monitoring, such as acoustic emission, electromagnetic radiation monitoring, and comprehensive full-time monitoring of roadway, to conduct long-term online monitoring on the changes of physical parameters of coal and gas. By analyzing the abnormal fluctuation of data, real-time warning of outburst accidents can be achieved [2732]. However, both the mathematical methods and the direct monitoring methods belong to the passive defense of large-scale prediction and real-time warning of the accidents. They fail to calibrate the potential risk factors that may lead to outburst accidents, making it difficult to achieve active defense.

In the actual management of coal seams with outburst hazards, the following methods are adopted. A large number of boreholes are constructed in the working face, and the floor roadway cross-layer drilling is used to drain the strip gas in the mining roadway, and the along-layer drilling is used to drain the gas in the recovery area [33]. Coal seam gas drainage can reduce coal seam gas content and pressure, thus eliminating the outburst hazards. Therefore, over 100,000 meters, or even hundreds of thousands of meters of boreholes, need to be constricted in a mine every year. During drilling, a large number of drill cuttings will be generated upon the exposure and crushing of coal, an original occurrence state when coal is crushed. Thus, the particle size distribution characteristics and mechanical characteristics of drill cuttings can comprehensively reflect the in situ occurrence state of coal, and much geological information of gas in coal seams can be obtained by theoretical inversion. On this basis, Lv et al. [34] proposed a new method to predict the position of tectonically deformed coal in horizontal wells by studying the particle size distribution of drill cuttings during the development and drilling of coalbed methane wells. Moreover, they verified the effectiveness of the method by comparing the coal seam structure with the prediction results at corresponding moments of coal seam recovery. Zhou et al. [35] collected drill cuttings of boreholes at different depths and studied the distribution of drill cuttings particle size with drilling depth in a deep coal seam. It was found that the particle size distribution of drill cuttings could effectively reflect the changes of ground stress and gas content in a coal seam.

The purpose of this study is to use the characteristic data of drill cuttings that have not been used in daily production, to solve the problem of coal and gas outburst detection around medium and small faults in the production process. First, the principle of drilling and crushing of gas-containing coal was summarized. Next, regarding the characteristics of coal seams such as low gas mine, outburst mine, and soft and hard coal, statistical analysis was carried out on drill cutting samples at different relative positions of faults. Furthermore, the geometric characteristics, such as the characteristic function of drill cuttings particle size distribution and average particle size, and the mechanical characteristics, such as particle strength and hardness coefficient, were discussed. Finally, by analyzing the existing operation process data, an effective method to explore the risk factors of outburst accidents was obtained, thus making up for the shortcomings of exploration technology and realizing active defense.

2. Theoretical Basis

2.1. Drilling Crushing Mechanism of Coal

The drilling by drilling tools in coal rock can be regarded as the result of the combined action of axial forward and radial rotation. The change of axial borehole depth is mainly determined by the feed force acting on the drilling tool. As shown in Figure 1, the unit pressure on the contact surface between the drilling tool and the rock should be greater than the indentation hardness of the rock: where is axial load, is indentation hardness of the rock, and is the contact area between the cutting edge and the rock.

When the drill edge is pressed into the coal, the drilling process can be simplified as the interaction between the circular cemented carbide composite plate and the coal rock. During this period, the pressure on the contact surface is unevenly distributed, and its value represents a function that decreases with the increase of the distance from the pressure point to the center of the pressure surface:

It can be known that at the center of the pressure surface, , at the pressure edge .

Therefore, as shown in Figure 2, according to the different effective forces of cutting tools on coal rock, the drilling and crushing process of coal rock under the original occurrence conditions is divided into the following three stages: (1)Surface crushing: as the effective force of drilling tool on coal rock is far lower than the hardness of coal rock, the blade fails to be pressed into coal rock. The drilling tool crushes the coal rock by grinding, and the drill cuttings are powder. At this time, the drilling rig works in a very low drilling speed, which not only seriously affects the production efficiency but also increases the wear of drilling tools, thus increasing the production cost [36](2)Ductile crushing: as the axial load on the drilling tool increases, the effective force is still less than the hardness of the coal rock. The drilling tool has not drill deep into the coal rock (usually less than 1 mm in medium strength). At this time, the drilling speed slightly increases, and the matrix structure and grain depolymerization of coal rock occur [37], which enables the defects between rock structures to develop, especially the fatigue cracks generated by multiple loading at the bottom of the hole. Consequently, cracks are interlaced, and the drill cuttings are mainly small-sized particles(3)Brittle crushing: the load on the cutting tool continues to increase, and the effective force is greater than or equal to the hardness of coal rock. The drilling tool succeeds in cutting into the coal rock. At this time, the drilling speed greatly increases, and the structure of coal rock is constantly damaged. Macrocracks begin to form from the tip of the edge and expand unstably to the distal end. Then the drill cuttings strip off from the rock in flake [37]

2.2. Theory of Gas-Containing Coal’s Strength

The macroscopic characteristics of drill cuttings are not only restricted by construction technology, but also closely related to the physical and mechanical properties of coal. Previous studies [38] on the mechanical properties of gas-containing coal disclose that in the absence of gas, the average strength of coal is 32.41 MPa, and the average elastic modulus is 2.132 GPa, showing an overall brittle failure property. When the gas pressure is 1 MPa, the average strength is 24.629 MPa, with a decline of 24%. When the gas pressure is 2 MPa, the average strength is 20.234 MPa, 17.84% lower than that under 1 MPa gas pressure and 37.57% lower than that under no gas pressure, exhibiting an obvious decrease in strength. In addition, as the gas pressure rises, the coal sample in the saturated adsorption state steps into an obvious initial compaction stage on the stress-strain curve. The elastic stage becomes shorter, and the elastic modulus increases accordingly. The average elastic modulus of the coal sample is 1.85 GPa under 1 MPa gas pressure and 1.569 GPa under 2 MPa gas pressure, 12.86% and 26.1% lower than that under no gas pressure, respectively. The existing theory mainly explains the effect of gas on coal strength from two aspects.

On the one hand, according to the principle of effective stress, the free gas in the fractures not only expands the coal and reduces the density of coal, but also provides the counteracting force of confining pressure. According to the Colombia strength criterion, the compressive strength of coal decreases with the decrease in effective confining pressure [39, 40]. where is the triaxial compressive strength of coal, is the uniaxial compressive strength of coal under complete shear failure, is the confining pressure of coal, and is the coefficient.

On the other hand, under the nonmechanical effect of gas adsorption, the tension on the surface of microporous fractures in the matrix decreases, resulting in the decrease in the attraction between coal molecules and the weakening of the ability of matrix to constrain coal molecules. Furthermore, the coal matrix expands and deforms. Macroscopically, the cohesion between coal particles is reduced, which eventually leads to the decrease in the force and energy required for the instability and failure of coal [41, 42]. Consequently, the peak strength and peak strain decrease. Wang [43] believed that adsorbed gas could wedge into microcracks in the coal to make the coal swell and relax then weakens the bond between coal particles and leading to a decrease in coal strength. The Soviet scholar Astakhov and Khazov [44] held that the adsorbed gas produced a capillary condensation effect within the microfractures of coal, thus reducing the strength of coal. Yao and Zhou [45] explained the effect of adsorbed gas on coal strength based on the Rehbinder effect theory as well as the Griffith fracture criterion. The fracture toughness of coal fracture is related to its surface free energy : where is the initial length of the fracture (m).

After the coal adsorbs gas, the surface free energy of the coal decreases, and the fractures are more likely to expand. Overall, it is manifested by a decrease in the compressive strength of the coal. A higher gas pressure accounts for a greater amount of gas absorbed. Consequently, the surface free energy of the coal drops more notably and the strength of the coal becomes lower.

3. Sampling and Laboratory Testing

China’s geological conditions are complex, and there are great differences in coal forming conditions and storage environment in different regions, resulting in thousands of different associated faults. In order to explore the law of cutting characteristics of coal seams under different conditions, Luling Coal Mine, Yuenan Coal Mine, and Sihe Coal Mine are selected as the sampling subjects (Figure 3). There are 5 boreholes inside the working faces of 63011 and 63013 roadways of Sihe Coal Mine, 3 boreholes in the intake airway of 215101 working face of Yuenan Coal Mine, and the 10# coal seam of Luling Coal Mine, respectively. The completion parameters of each borehole are given in Table 1. During construction, the drilling stopped when the tool reached the sampling depth, then the water was continuously pumped until no obvious cutting could be found in the returning water. Then, the feeding pressure of the drilling rig and the water pressure were adjusted to 5 MPa and 0.78 MPa, respectively, and the drilling proceeded for 1 m. The cuttings discharged from the orifice were collected, and then a coal seam gas content test was carried out.

The collected drill cutting samples were naturally dried according to Sinopec Northwest Oilfield Company Enterprise Standard (Q/SHXB0092-2012). The drill cutting samples were weighed every 24 h until the difference between the two weighing data was less than 10 g. Then, the drill cutting samples were regarded as fully dried cuttings. Among the prepared groups of drill cutting samples, those coagulated due to drying were dispersed, screened with the standard sample screening (8 mm, 4 mm, 2 mm, 1 mm, 0.5 mm, 0.25 mm, 0.125 mm, and 0.074 mm), weighed, and sealed for particle geometry analysis.

As mentioned above, drill cuttings are a kind of fine coal rock particles formed by the fracture penetration under the combined action of compression load and shear load. Therefore, their morphological characteristics and particle mechanical properties are closely related to the mechanical properties of coal rock mass. Thus, in this paper, the particle strength, a basic mechanical index to study the compressive load of the sample in situ conditions [46], is tested by randomly selecting 100 nearly spherical drill cuttings whose size ranges from 1 mm to 4 mm. The test device is illustrated in Figure 4. However, due to the small size of the collected drill cutting samples, it is impossible to carry out the determination of shear strength. Therefore, the value of each sample is counted as a measure of the resistance of the sample to external energy damage under the combined load.

4. Result and Discussion

4.1. Geometric Characteristics of Drill Cuttings

The geometric characteristics of particles are important parameters to describe the particle size composition of particle groups. The research on them often starts from the following three aspects: particle size distribution, cumulative mass distribution, and distribution characteristic model.

Particle size distribution, also known as dispersion, refers to the quality or quantity of particles in different particle size ranges. Figure 5 is the histogram of mass distribution accumulation of samples. The particle size distribution of all samples showed the characteristics of normal distribution. Among them, LL-2, LL-3, YN-3, SH-1, SH-5, and SH-8 samples near the fault show the peak particle size range and median particle size range of large particles. Then the cumulative mass distribution of each sample is converted to the curve shown in Figure 6. We can find that the curves of SH-1, SH-5, and SH-8 are linear functions, and all other curves are approximately logarithmic functions. For example, LL-2, LL-3, and YN-3, the bending degree of its curve is significantly less than that of other samples. The reason is that the formation of faults destroys the integrity of the coal seam; then the coal in the fault zone is squeezed and rubbed, which expands the adsorption area of the coal, creates conditions for storing a large amount of gas, and strengthens the adsorption capacity of coal [3]. Therefore, compared with the normal coal seam, this area is prone to local accumulation of gas. Under the same reservoir conditions, a high content of gas greatly weakens the strength of the coal. Therefore, its ability to resist external energy damage is weakened, and compared with the normal drilling process of coal, the biting depth of drilling tools is relatively large [47], and the crushing process is more similar to brittle crushing in Figure 3, which tends to produce large drill cuttings. It can be seen that during drilling near the fault, the coal fractures at the bottom of the hole are more likely to develop, making the particles with large particle size predominate in the drill cuttings.

Statistically, the average value of sample data is usually used to eliminate the deviation of the number of data from the total number and the single data, and it reflects the overall trend of data concentration. The test results are solved by the average particle size of drill cuttings specified in the national standard GB/T15445.2-2006, and the average particle size of each drill cutting sample is analyzed by the formula: where is average particle size of the sample, is median particle size of the th particle size range, and is particle mass percentage of the th particle size range.

Figure 5 shows the histogram of the average particle size of each sample. It can also be found that the average particle size of fault damage zone samples is much higher than that of other samples, and the maximum value is 3.9 times higher than the minimum value. It indicates that the strength of coal in this area is relatively low, and the average particle size of drill cutting sample is likely to increase abnormally under the action of external load. On the one hand, the sampling points are located in the damage zone between two faults, and the coal increases in fragmentation and decreases in strength under the action of uneven extrusion stress. On the other hand, the coal seam position of these sampling points is relatively thick due to tectonic movement, which means a longer distance of gas migration to the roof and floor. In addition, the low permeability of the coal seam corresponds to a large gas diffusion resistance and hinders gas diffusion. Resultantly, the gas content rises locally, which weakens the strength of the coal and reduces its ability to resist crushing [48]. Moreover, compared with normal hard coal, the coal near the fault contains more vigorously developed fractures and is less susceptible to disturbance. Thus, it has better gas confinement conditions and is prone to local accumulation of gas and coal and gas outburst hazards [49], threatening production safety.

The particle size distribution model is often adopted in the study on granular particles to quantitatively characterize the particle size distribution. Among characterization models, the Rosin-Rammler distribution model is more suitable than others for the particle characteristics obtained by operations including grinding and impacting and for the particle size distribution characteristics of spray droplets. The equation is as follows: where is cumulative distribution of particle size, is particle size (mm), is characteristic particle size, and is distribution modulus.

Based on the above equation, the function fitting is performed on each sample to obtain the calculation results (Figure 7). It is found that LL-2, LL-3, YN-3, SH-1, SH-5, and SH-8 still show the above-mentioned specific phenomena, and the characteristic particle sizes of the samples near the fault are significantly smaller than that of the normal coal seam.

In this study, the nonuniformity coefficient and curvature coefficient in soil mechanics are introduced to further describe the uniformity of drill cuttings [48], where , , and are the constrained particle size of 60%, 30%, and 10% on the cumulative particle size distribution curve.

As shown in Figure 8, in all samples of the three mines , . According to the relevant data of soil mechanics, the drill cuttings of these boreholes have good uniformity and good gradation. And and of LL-2, LL-3, YN-3, SH-1, SH-5, and SH-8 near the fault are greater than the normal coal seam samples of the mine. Among the sampling points with abnormal particle size of drill cuttings mentioned above, of the hard coal samples in Sihe Coal Mine, an outburst coal mine, is 0.19~0.21, and is 1.36~1.49, both of which are small than most boreholes, indicating that the abnormal increase in gas content is conducive to the uniformity of drill cuttings. However, Luling Coal Mine and Yuenan Coal Mine do not show abnormal phenomena. Therefore, under the current sample size, it can be considered that the variation of nonuniformity coefficient and curvature coefficient cannot be used as a decisive indicator to determine the existence of faults.

In conclusion, it can be found that for both soft coal and hard coal in an outburst mine and a nonoutburst mine, during coal seam drilling, when the bottom of the hole is too close to the fault, the drill cuttings will display good particle gradation, high proportion of large particle size, abnormal increase in average particle size, peak particle size range of large particle size, median particle size range of large particle size, and not changing regularly in Rosin-Rammler distribution function distribution modulus, but there are no obvious pattern and phenomenon for particle’s nonuniformity coefficient and curvature coefficient.

4.2. Mechanical Characteristics of Drill Cuttings

Figure 9 shows the scatter diagram of uniaxial compressive strength test of sample particles. The test results are statistically analyzed by the SPSS software, and the results are shown in Table 2. It can be found that though the samples from the same mine are taken at different positions of the coal seam, the particle strength fluctuates in a small range. There is no obvious correlation between particle strength and particle size, showing a tendency of approximate concentration. The test results of the geometric characteristics of drill cuttings disclose that the LL-2, LL-3, YN-3, SH-1, SH-5, and SH-8 drill cutting samples near the fault contain a large proportion of coarse particles, and the particle strength of these groups of samples is generally greater than that of other samples in the mine. Combined with the test results of gas content, it can be concluded that the abnormal fluctuation of the bonding characteristics of drill cuttings is closely related to the local accumulation of gas.

Figure 10 shows the statistical results of value (a physical quantity specially used to measure the firmness of coal in the coal industry). The value of Luling coal mine sample is basically the same. The value of YN-3 in Yuenan coal mine sample is the lowest, but it is only 0.04 lower than YN-2 with the largest value, the minimum value of SH-1 between different faults and located in the fracture zone is 1.02. According to the research results of literature [50, 51], the permeability of gas-containing coal is proportional to the value of coal. The LL-2, LL-3, YN-3, SH-1, SH-5, and SH-8 samples are collected near the fault, and the coal continuity and integrity at the sampling points are destroyed, so that the gas occurrence in the coal seam alters. A comparison of coal seam gas content determination results reveals that the gas at these three sampling points is well sealed. The coal rock will be disturbed by operations, including mining, blasting, and drilling. Consequently, the original stress balance will be destroyed and transferred. When the external disturbance stress exceeds the ultimate bearing capacity of the coal, over time and under the external stress, the weak structure is prone to accidents. Therefore, during mining, it is necessary to carry out targeted production measures to reduce the probability of accidents at the points of abnormal changes of drill cuttings in the coal seam boreholes.

4.3. A Method of Predicting Outburst Based on the Drill Cutting Characteristics

Among the parameters studied above, some indirectly reflect the occurrence of coal seam gas under in situ conditions, some reflect the stress state of coal seam, and some reflect the mechanical properties of coal seam. There is an internal relationship between these variables hidden behind the data. They exhibit a complexity and nonlinearity, which is what neural networks are made for in problems analysis [52]. Therefore, the neural network is used to analyze the weights of the drill cutting characteristics indexes discussed above [53]. It is expected to find out the priority ranking of each test index when the drill cutting characteristics proposed are used to determine the existence of fault.

Using the multilayer perceptron neural network module of the SPSS software [54], take the quantity of drill cuttings, average particle size, characteristic particle size, distribution modulus, nonuniformity coefficient, curvature coefficient, particle strength, and value as the input signal, and see whether there is a fault as the output signal (1 represents presence and 0 represent absence). The information of network is shown in Table 3 and Figure 11. The architecture is set to automatic selection (the software can make the most appropriate settings for the model according to the data characteristics), the minimum number of units in the hidden layer is 1, the maximum number of units is 50.10 groups of data are used for model training, 6 groups of data are used for model examining. The hyperbolic tangent function is used as the activation function, the standardized method is used to scale the covariates, and softmax is used as the activation function of the output layer. In the process of training, the cross entropy error is 0.262, and the prediction error rate is 0. In the process of verification, the cross entropy error is 1.476, and the prediction error rate is 16.7%.

Figure 12 shows the weight analysis results. Among them, the index of average particle size has the greatest influence on fault detection, which is 100%, the quantity of drill cuttings is 78.9%, the characteristic particle size of Rosin-Rammler is 66.4%, the value is 61.5%, the particle strength is 55.9%, the distribution modulus of Rosin-Rammler is 51.8%, the curvature coefficient is 31.7%, and the nonuniformity coefficient is 25.6%. The results show that in case of abnormal change of drill cuttings’ particle size in the field construction, priority should be given to the average particle size of drill cuttings and the value for determining whether the phenomenon is caused by the existence of potentially hazardous objects in the coal seam or by the mutation of physical parameters of the coal seam.

5. Conclusions

In this paper, the characteristics of drill cuttings at the sampling points of fault and of different spatial positions were investigated based on the basic principles of geotechnical drilling engineering and the strength theory of gas-containing coal. Furthermore, the drill cutting samples of typical outburst mines with soft coal, low gas mines with hard coal, and outburst mines with hard coal were collected. Meanwhile, researches are conducted on the production site and in the laboratory. The main work and conclusions are as follows: (1)Compared with normal coal seams, the drill cuttings near the fault sampling point show large average particle size, low Rosin-Rammler characteristic particle size, good particle grading, and uniformity in terms of geometric characteristics. In terms of mechanical characteristics, it shows high particle strength and value(2)The formation of the fault destroys the integrity of the coal seam and reduces its strength. Therefore, during the drilling process, the fracture forms of the coal body are mainly surface crushing and brittle crushing. However, the experimental results are contrary to the theory, and there are more large-size particles. It can be considered that the existence of the fault leads to the accumulation of gas in the coal seam and the decrease of the strength of the coal body(3)With the help of neural network analysis, it is concluded that in the process of field application, if there is an abnormal change in the particle size of drill cuttings, the weight of each research variable is average particle size > quantity of drill cuttings > the Rosin-Rammler characteristic particle size > value > particle strength > the Rosin-Rammler distribution modulus > curvature coefficient > nonuniformity coefficient. Limited by the volume of existing research data, the author will further expand the sampling range to enrich the research conclusions

Data Availability

The data in the paper was obtained from the experiment.

Conflicts of Interest

All authors in this paper declare that there are no conflicts of interest regarding the publication of this article.


This research was financially supported by the National Natural Science Foundation of China (No. 51874297) and the Postgraduate Research & Practice Innovation Program of Jiangsu Province (Grant KYCX21_2471).