A comprehensive study on in situ stress field characteristics and changes in rock mechanical properties in deep mines in northeastern Yunnan, China-深地科学

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A comprehensive study on in situ stress field characteristics and changes in rock mechanical properties in deep mines in northeastern Yunnan, China

Abstract

The Maoping lead–zinc mining area is a significant metal mine site in northeastern Yunnan. In this study, both hydraulic fracturing in situ stress testing and ultrasonic imaging logging were first carried out in the mining area. Second, 930 focal mechanism solutions and 231 sets of stress data near the mining area were collected. Then, the variations in the type of in situ stress field, the magnitude of in situ stress, the direction of horizontal principal stress, and the ratio of lateral pressure were analyzed to characterize the distribution of the in situ stress field. On this basis, a new method using borehole breakouts and drilling-induced fractures was proposed to determine the stress direction. Finally, the evolution of the mechanical properties of dolomite with burial depth was analyzed and the influence of rock mechanical properties on the distributions of the in situ stress field was explored. The results show that the in situ stress in the mining area is σH > σV > σh, indicating a strike–slip stress state. The in situ stress is high in magnitude, and its value increases with burial depth. The maximum and minimum horizontal lateral stress coefficients are stabilized at approximately 1.22 and 0.73, respectively. The direction of the maximum horizontal principal stress is NW, mainly ranging from N58.44° W to N59.70° W. The stress field inferred from the focal mechanism solution is in good agreement with the test results. The proportion of structural planes with dip angles between 30° and 75° exceeds 80%, and the dip direction of the structural planes is mainly NW to NWW. The line density of structural planes shows high density in shallow areas and low density in deep areas. More energy tends to be accumulated in rocks with higher elastic modulus and strength, leading to higher in situ stress levels. These findings are of significant reference for mine tunnel layout, support design optimization, and disaster prevention.

Highlights

Based on the in situ stress measurements, the in situ stress field characteristics of the Maoping lead–zinc mining area and adjacent areas were obtained.
A new method using borehole breakouts and drilling-induced fractures was proposed to determine the stress direction.
The evolution of the mechanical properties of dolomite with burial depth was analyzed and the influence of rock mechanical properties on the distributions of the in situ stress field was explored.

1 INTRODUCTION

Yiliang County of Zhaotong City, located in the northeast of Yunnan Province, is a typical representative of strong seismic activity in mainland China. According to statistics, since 1900, there have been 32 earthquakes exceeding magnitude 5.0 in Zhaotong, resulting in a total of 4142 deaths and 5046 injuries. The magnitude 6.5 earthquake in Ludian in 2014 caused 617 deaths and 3143 injuries (He et al., 2023). Engineering geological hazards, crustal fault sliding instability, and seismic activity are closely related to the changes in in situ stress state and rock mechanical properties (Li et al., 2019; Rajabi et al., 2016). Therefore, it is very important to explore in situ stress and rock mechanical properties in Zhaotong.

In-stress state can be measured through various techniques, such as hydraulic fracturing, overcoring, and acoustic emission. In-depth research on the in situ stress state in various regions worldwide has been conducted based on measured stress data (Chen et al., 2023; Heidbach et al., 2018; Li & Cai, 2022). Worotniki and Denham (1976) established a linear regression relationship between the average horizontal principal stress and the vertical principal stress with depth. Brown and Hoek (1978, 1980) utilized in situ stress measurements worldwide to obtain the distribution characteristics of in situ stress with depth. Xie, Gao, and Ju (2015) analyzed in situ stress distribution maps from more than 30 countries and reported that the shallow in situ stress state is dominated by tectonic stress, while the deep in situ stress state gradually transitions to a hydrostatic pressure state. Kang and Gao (2024) analyzed the distribution characteristics and influencing factors of the underground stress field in Chinese coal mines based on extensive field measurements of in situ stress. Li and Miao (2017) depicted the characteristics of the in situ stress field at the burial depth of the metal mining area in China based on 165 sets of measured in situ stress data and discussed the stability of the fault in a Chinese metal mining area from the perspective of in situ stress. As the mining depth increases, geological conditions become more complex, resulting in engineering disasters such as rock bursts, large deformations of surrounding rocks, and rheological deformations. An increase in the stress level and a change in the stress state are the fundamental causes of these engineering disasters (He et al., 2005; Xie, Gao, Ju, Gao, and Xie, 2015). The in-stress state is inevitably influenced by the mechanical properties of the rock mass, and inversely, the changes in the in situ stress state affect the properties of the surrounding rocks. In addition to showing an obvious linear relationship with depth, in situ stress is also closely related to lithology and rock mass structure (Anderson, 1951; Miao et al., 2016; Ning et al., 2022). The physical and mechanical properties of rock mass, such as strength, elastic modulus, and Poisson's ratio, directly influence the magnitude and distribution of in situ stress (Lu et al., 2021; Zhu et al., 2022).

The above studies mainly used a single technique to determine the in situ stress field. Haimson (2010) pointed out that all in situ stress testing methods have limitations. For example, the overcoring method can only be applied to intact rock, with significant limitations on the measurement depth (Han, 2019). As drilling depths increase, hydraulic fracturing measurement equipment may be limited by temperature and pressure (Cornet et al., 1997). The theoretical basis of the acoustic emission method is not solid enough, and its accuracy is greatly affected by parameter settings and background noise (Lehtonen & Särkkä, 2006). Due to the limitations of any single technique, it is generally recommended to integrate multiple types of stress data so as to improve the reliability of in situ stress measurement. In addition, there are currently few supporting studies on the relationship between rock mechanical property changes and in situ stress state distributions, which means that a comprehensive study is in need.

Therefore, this study explored the distribution characteristics of the current in situ stress field in northeast Yunnan Province by using multisource stress data, including in situ stress measurements, focal mechanism solutions, and borehole damage information, so as to comprehensively determine the in situ stress magnitude and direction in the mining area. Based on the borehole ultrasonic imaging test results, a new method using borehole breakouts and drilling-induced fractures was proposed to determine the stress direction, and a statistical analysis was conducted on the dip direction, dip angle, and line density of structural planes. Through rock mechanics experiments, the evolution of rock mechanical properties with depth was studied, based on which the influences of rock mass structure and rock mechanical properties on in situ stress were explored.

2 ANALYSIS OF THE IN SITU STRESS FIELD IN THE MINING AREA

2.1 Geological setting and measurement scheme

The Maoping lead–zinc mine is situated in the southern section of the seismic zone extending from southwest Sichuan Province to northeast Yunnan Province. The terrain within the mining area is characterized by steep slopes, with a maximum ground elevation of 2075 m and a minimum of 887 m. The structural activity in the mining area is strong, with the primary structure being the Shimenkan anticline, accompanied by two sets of fault structures trending NE‒SW and NW–SE. In addition, in the deep west wing of the Shimenkan anticline, interlayer faults, and interlayer sliding structures have developed due to external force extrusion from the northwest to southeast, which results in the formation of a complex structure. The lead–zinc ore body occurs in dolomite and is divided into three formations based on lithology and ore-bearing characteristics: $D_{3}^{3 - 1}$ , $D_{3}^{3 - 2}$ , and $D_{3}^{3 - 3}$ . To analyze the in situ stress state and rock structure characteristics of the Maoping lead–zinc mining area, hydraulic fracturing in situ stress tests were conducted in borehole SBDZK96-1 so as to obtain the in situ stress in the mining area. Additionally, the ABI40 integrative acoustic borehole imaging system was used to scan boreholes SBDZK96-1 and SBDZK86-2 to obtain detailed data on the joints and fissures in the borehole walls. Rock mechanics tests were conducted using the TAW2000 rock mechanics test machine to explore the correlation between rock mechanical properties and in situ stress. The TAW2000 has an automatic data acquisition system that can simultaneously record testing parameters such as load, stress, displacement, and strain. Axial and circumferential extensometers were used to measure the deformation of the rock samples during the tests. As shown in Figure 1, all the cylindrical specimens have a diameter of 50 mm and a length of 100 mm, with a length-to-diameter ratio of 2 in accordance with the International Society for Rock Mechanics (ISRM) standards.

Details are in the caption following the image — Figure 1
Open in figure viewer PowerPoint

Dolomite specimens in formations $D_{3}^{3 - 1}$ , $D_{3}^{3 - 2}$ , and $D_{3}^{3 - 3}$ .

2.2 Comprehensive analysis of in situ stress field characteristics

2.2.1 The distribution of the in situ stress field

In hydraulic fracturing measurements, the vertical principal stress (σV) is estimated from the weight of the overlying strata (the density of the rock: 2.73 g/cm3). The variations in horizontal principal stress with burial depth are shown in Figure 2. The maximum horizontal principal stress (σH) ranges from 22.07 to 30.04 MPa, the minimum horizontal principal stress (σh) ranges from 13.19 to 17.03 MPa, and the σV ranges from 18.77 to 21.15 MPa. All the maximum principal stresses exceeding 20 MPa indicate that the in situ stress is at a high stress level. Both σH and σh increase gradually with depth, but the discreteness is significant, which can be mainly attributed to the dense distribution of numerous faults and fracture structures in the mining area. The movement of fault structures causes stress release, and multiple measurement points are located near large-scale fault zones; thus, in situ stress values are abnormal. The relationships among the three principal stresses are σH > σV > σh, which is a typical tectonic stress field. According to Anderson's fault theory (Anderson, 1951), this area has a strike–slip stress structure that is conducive to the development of strike–slip faults. The maximum and minimum horizontal lateral pressure coefficients are represented as kH = σH/σV and kh = σh/σV, respectively. The kH varies from 1.09 to 1.44, with an average of 1.22, and the kh varies from 0.65 to 0.81, with an average of 0.73. The σV is approximately equal to the weight of the overburden rock.

The direction of the maximum horizontal principal stress is crucial for determining the direction of tunnel excavation in mining areas. However, the hydraulic fracturing method cannot effectively determine the direction of in situ stress. Therefore, this study proposed the following exploratory approach to determine the stress direction through borehole breakouts and drilling-induced fractures. A schematic diagram of borehole breakouts and drilling-induced fractures is shown in Figure 3. Ultrasonic imaging logging tests were carried out in boreholes SBDZK96-1 and SBDZK86-2. The typical features of borehole breakouts in the two boreholes are shown in Figure 4. The dark blue strips formed by borehole breakouts can be clearly observed, indicating that there is an obvious borehole breakout phenomenon in the two boreholes.

WellCAD software was used to obtain the azimuth distribution characteristics of the borehole breakouts (Figure 5). The collapse directions in both boreholes are concentrated in the NE‒SW direction. The average collapse azimuths for boreholes SBDZK670-86-2 and SBDZK670-96-1 are 36.42° (213.24°) and 29.85° (214.68°), respectively. Due to the concentration of compressive stress around the borehole, compressive shear failure occurs on the borehole wall, resulting in the phenomenon of elliptical boreholes. Therefore, the development direction of borehole breakouts is perpendicular to that of the maximum horizontal principal stress. The direction of the maximum horizontal principal stress is shown in Figure 6. The predominant orientation of the maximum horizontal principal stress for both boreholes is NW‒SE. The average orientation of borehole SBDZK96-1 is 301.36°, that is, N58.64° W (Figure 6a). The average orientation of borehole SBDZK86-2 is 301.56°, that is, N58.44° W (Figure 6b). Collapses usually occur at depths greater than 1000 m (Wang et al., 2014). Borehole breakout phenomena occurred simultaneously in two boreholes at 670 m in the Maoping lead–zinc mine, further indicating that the Maoping lead–zinc mine is a high-stress field area, which corresponds to the test results of the hydraulic fracturing method.

Some scanning images also reveal drilling-induced fractures in the borehole wall. The concentration of tensile stress on the borehole wall leads to tensile failure of the borehole wall. Therefore, the direction of tensile cracks in the borehole wall is generally consistent with that of the maximum horizontal principal stress. Ultrasonic borehole televiewer logging images at different depths are shown in Figure 7. The fracture surface is basically parallel to the borehole axis, and the directions of the maximum horizontal principal stress from shallow to deep layers are 297.7° (N62.3° W), 294.2° (N65.8° W), and 309.1° (N50.9° W). This indicates that the direction of the maximum principal stress near the measuring point is N50.9° to 65.8° W and the average direction is N59.7° W.

2.2.2 Inversion of the in situ stress field in a mining area based on focal mechanism solutions

As shown in Figure 8, a total of 930 focal source mechanism solutions were collected for earthquakes with magnitudes of 2.5 ≤ Ms ≤ 7.4 in the mining area (N25.5°–29.5°, E102°–106°) since 1970. Statistical analysis indicates that the predominant orientation of the P-axis in the mining area is NW (Figure 9).

The focal mechanism solutions were categorized based on the classification criteria proposed by Zoback (1992). According to the inversion results of the focal mechanism solutions for the 930 earthquake records, 108 events were classified as the normal faulting type, accounting for 11.6%; 348 events as the strike–slip type, accounting for 37.4%; 276 events as the reverse fault type, accounting for 29.7%; and 198 events as unknown type, accounting for 21.3%. Therefore, the focal mechanism solutions of the mining area predominantly show strike–slip and reverse fault characteristics.

The stress inversion script developed by Vavryčuk (2014) was used to invert the regional tectonic stress field distribution and stress shape factor (R) reflected by the focal mechanism solutions in the mining area. The results are shown in Figure 10. The orientation of the maximum principal stress axis in the mining area is approximately 120.18° ± 0.67°, with a dip angle of approximately 1.18°, which is nearly horizontal. The orientation of the intermediate principal stress axis is approximately 210.53° ± 7.84°, with a dip angle of approximately 16.54°, which is also nearly horizontal. The orientation of the minimum principal stress axis is approximately 26.23° ± 7.84°, with a dip angle of approximately 73.42°, nearly vertical. Therefore, the in situ stress in the mining area is dominated by reverse faulting. R in the mining area is approximately 0.96, indicating a close relationship between the intermediate principal stress and the minimum principal stress.

To obtain the in situ stress field in the Maoping lead–zinc mining area and adjacent areas, a total of 231 sets of stress data were collected in the mining area, including 120 sets of direction data. The advantage range of the measured stress in the regional range is from N120° to 160° E (Figure 11). The maximum principal stress direction obtained from two borehole breakouts is on average N58.44° W and N58.64° W, respectively, and the maximum principal stress direction obtained from drilling-induced fractures in one borehole is N59.7° W on average. Therefore, the direction of in situ stress obtained using the new method is consistent with the occurrence law of in situ stress in the mining area.

2.2.3 Determination of the lateral pressure coefficient in the mining area

In general, the in situ stress values are discrete, and linear fitting methods cannot be used to effectively normalize these discrete data. The Sheorey model is a static viscoelastic thermal stress model that can normalize in situ stress values. For the same structural area, the following equation and in situ stress values can be used to predict the in situ stress state with different lithologies and burial depths (Wang et al., 2014).

k_{2} = k_{1} \frac{0.25 + 7 E_{rm 2} (0.001 + \frac{1}{Z_{2}})}{0.25 + 7 E_{rm 1} (0.001 + \frac{1}{Z_{1}})},

(1)

where Z 1 and Z 2 denote the burial depths; k 1 and k 2 are the average lateral pressure coefficients at depths Z 1 and Z 2, respectively; and E rm1 and E rm2 denote the elastic modulus of the rock mass at depths Z 1 and Z 2, respectively.

Equation (1) presents the modified Sheorey model, which considers two parameters: the burial depth Z and the elastic modulus Erm of the rock mass. Erm is a parameter that varies with burial depth and includes information such as lithology and structural planes. The modified Sheorey model can effectively fit and predict the variation trend of the in situ stress distribution with depth and location. In addition, k reflects the fault stress state and the information of the Anderson fault theory. Therefore, the modified Sheorey model can accurately predict the in situ stress state in deeply buried engineering areas.

According to the modified Sheorey model, the lateral pressure coefficients were fitted to the 231 sets of stress data and measured data. The fitting formula is shown in Equations ( 1) and ( 2), and the fitting results are shown in Figure 12. These characteristics are generally similar to those of the Hoek‒Brown relationship curve (Brown & Hoek, 1978). The stress field characteristics obtained from drilling measurements in the Maoping lead–zinc mine are consistent with the current in situ stress field in the mining area. The differences in the results reflect the variations in lithology and structural location at different measurement points. This illustrates the feasibility and reliability of fitting Equations ( 2) and ( 3). When the burial depth exceeds 200 m, the discreteness of the lateral pressure coefficient begins to decrease, and the stress is less affected by the topography. For the sake of conservatism, the average lateral pressure coefficient at approximately 400 m is used as the baseline for subsequent stress prediction. Through the fitting formula, the lateral pressure coefficients at 400 m are calculated to be k H = 1.70 and k h = 0.93. Using these side pressure coefficients as a reference, combined with laboratory rock mechanics test results and lithological conditions of the engineering area, the in situ stress values at different depths and lithological conditions can be predicted.

k_{H} = \frac{377.84}{Z} + 0.63,

(2)

k_{h} = \frac{186.84}{Z} + 0.44,

(3)

where Z denotes the depth.

2.3 Borehole ultrasonic imaging results

2.3.1 Statistical results of the structural plane dip angle

The ultrasonic imaging data of boreholes SBDZK96-1 and SBDZK86-2 reflect the borehole wall conditions in the ranges of 13.40–391.10 m and 17.10–400.20 m, respectively. Using WellCAD software, 1704 and 1852 structural surfaces were identified. Table 1 shows the statistical analysis of the structural plane dip angles revealed through the two boreholes. Both boreholes are dominated by gentler dip angles, steeper dip angles, and steep dip angles. The steeper and steep dip angles of SBDZK670-96-1 account for 76%, with an average dip angle of μ = 55.37° and a standard deviation of σ = 13.19° (Figure 13a). The proportion of gentler, steeper, and steep dip angles in SBDZK670-86-2 exceeds 87%. The average dip angle of the structural surfaces is μ = 53.50°, with a standard deviation of σ = 14.66° (Figure 13b).

Table 1. Statistical results of the structural plane dip angles.

Dip angle type	SBDZK96-1		SBDZK86-2
Dip angle type	Number of structural planes	Proportion (%)	Number of structural planes	Proportion (%)
Extremely gentle dip angle (0° < α ≤ 15°)	8	0.47	8	0.43
Gentle dip angle (15° < α ≤ 30°)	68	3.99	94	5.08
Gentler dip angle (30° < α ≤ 45°)	248	14.55	419	22.62
Steeper dip angle (45° < α ≤ 60°)	708	41.55	713	38.50
Steep dip angle (60° < α ≤ 75°)	587	34.45	479	25.86
Extremely steep dip angle (75° < α ≤ 90°)	85	4.99	139	7.51

2.3.2 Statistical results of the structural plane dip direction

Figure 14 shows the distribution pattern of the structural plane dip directions for SBDZK96-1 and SBDZK86-2 under the same lithology and at similar depths. The center of the circle represents the 0° dip angle and the outer circle represents the 90° dip angle. The quadrants of the point distribution represent the dip direction, with darker colors indicating a greater concentration of structural planes in that direction. The dip direction of borehole SBDZK96-1 with different lithologies and depths is mainly in the NW direction, with a more pronounced concentration in the NWW direction. The structural plane dip direction of SBDZK86-2 is mainly NWW, and a few structural planes are densely distributed in the SSW direction, gradually shifting toward the SE direction with increasing depth. Therefore, the small-scale structural planes in the mining area are still controlled by NE-oriented faults and nearly NS-oriented faults. The dominant directions of the small-scale structural planes are completely consistent with that of the NE–SW mineralized structures within this area.

2.3.3 Analysis of structural plane line density

The line density of the structural planes was calculated at an interval of 10 m. Figure 15 shows the variation characteristics of the structural plane linear density of the two boreholes with depths for the same lithology. The overall structural plane line density of the two boreholes gradually decreases with increasing depth. This indicates relatively fragmented rock masses in the shallow parts of both boreholes. For borehole SBDZK96-1, the structural plane line density is significant in the depth ranges of 60–70, 170–180, and 190–200 m, all exceeding 7.2 lines/m. The joints are most densely distributed in the ranges of 17–100 and 170–210 m, while the rock mass quality in other depth intervals remains relatively good. Borehole SBDZK86-2 shows a high structural plane line density in the depth ranges of 100–110 and 130–140 m, with the maximum structural plane line density exceeding 9.0 lines/m. Below 140 m, the structural plane line density generally stabilizes at approximately five lines/m.

3 MECHANICAL PROPERTIES OF DEEP ROCK

3.1 Evolution of rock mechanical properties with burial depth

Drilling and coring were carried out in eight mining sections of the Maoping lead–zinc mine, spanning depths of 300–1500 m. Each mining section includes $D_{3}^{3 - 1}$ , $D_{3}^{3 - 2}$ , and $D_{3}^{3 - 3}$ formations. The physical and mechanical parameters of the dolomite were obtained through rock mechanics tests. These data provided a foundation for rock mass quality evaluation and stope structural parameter optimization.

3.1.1 Evolutions of dolomite density with burial depth

The evolution of dolomite density with burial depth is shown in Figure 16a. The natural density of dolomite in formations $D_{3}^{3 - 1}$ , $D_{3}^{3 - 2}$ , and $D_{3}^{3 - 3}$ ranges from 2.60 to 2.90 g/cm3. The difference in the natural density of the rock samples among the different formations is very small, and the natural density of the rock samples shows a linear downward trend with an increase in burial depth. As shown in Figure 16b, taking formation $D_{3}^{3 - 2}$ as an example, the natural density, dry density, and saturated density of dolomite all decrease linearly with an increase in burial depth. At the same burial depth, the numerical differences in the natural density, dry density, and saturated density of dolomite are very small, indicating that underground water has a relatively minor impact on the rock density.

3.1.2 Variations of uniaxial compressive strength (UCS) of dolomite with burial depth

Rock mass is the carrier of in situ stress, and its mechanical properties directly influence the distribution of in situ stress. The variations of UCS of dolomite with burial depth are shown in Figure 17. The UCS of dolomite in formations $D_{3}^{3 - 1}$ , $D_{3}^{3 - 2}$ , and $D_{3}^{3 - 3}$ are mainly between 10 and 60 MPa. The UCS of dolomite in formations $D_{3}^{3 - 1}$ and $D_{3}^{3 - 2}$ increases linearly with an increase in burial depth. There is a good correlation between in situ stress and rock compressive strength, indicating that the higher the strength of the rock mass, the greater the stored stress. The UCS of dolomite within the same formation is highly discrete, while the range of UCS between different formations is relatively consistent. The UCS of dolomite in formation $D_{3}^{3 - 1}$ is generally greater than that in formation $D_{3}^{3 - 2}$ . This phenomenon may be associated with the increase in microcracks inside the rock in formation $D_{3}^{3 - 2}$ due to mineralization and extrusion.

3.1.3 Variation characteristics of the elastic modulus and Poisson's ratio with burial depth

Due to differences in rock stiffness, stress discontinuities occur at interfaces between different rock layers. The elastic modulus, as an important parameter influencing the distribution of in situ stress, reflects the rock stiffness. The variation characteristics of the elastic modulus of dolomite with burial depth are shown in Figure 18. The elastic modulus of the dolomite in formations $D_{3}^{3 - 1}$ and $D_{3}^{3 - 2}$ increases linearly with burial depth, but that of each stratum changes slightly with burial depth. This is because the higher the elastic modulus of the rock formation, the more easily energy would accumulate, resulting in greater horizontal stress within the rock formation. Conversely, for soft and fractured rock formations with lower elastic modulus and less energy accumulation, the endured horizontal stress is also lower.

3.1.4 Dolomite tensile strength changes with burial depth

The changes in the dolomite tensile strength with burial depth are shown in Figure 19. The slope of the fitting curve for the dolomite tensile strength is close to zero. This indicates that the rock tensile strength remains approximately constant with an increase in burial depth. At the same burial depth, the tensile strength of dolomite is almost the same in formations $D_{3}^{3 - 1}$ and $D_{3}^{3 - 2}$ .

3.2 Triaxial compression test results for dolomite

Based on the above analysis of the physical and mechanical parameters of dolomite, the physical and mechanical properties of $D_{3}^{3 - 1}$ , $D_{3}^{3 - 2}$ , and $D_{3}^{3 - 3}$ formations are relatively similar. Therefore, formation $D_{3}^{3 - 1}$ was used as a representative to conduct triaxial compression tests of dolomite in its natural and saturated states. The shear strength parameters of dolomite were calculated based on the Mohr–Coulomb criterion. The results are shown in Table 2 for the natural state and Table 3 for the saturated state. The triaxial compressive strength of dolomite in the saturated state is significantly lower than that of the rock samples in the natural state, indicating that groundwater has a significant deterioration effect on dolomite, making saturated rock samples more prone to failure. The peak strength of dolomite increases as the confining pressure increases. This is because high confining pressure effectively suppresses tensile behavior at the crack tips inside the rock, thus inhibiting the expansion and penetration of microcracks. Under the same confining pressure, the peak strength of dolomite in the natural state gradually decreases with an increase in burial depth, while the peak strength of dolomite at different depths in the saturated state remains relatively close. This indicates that the peak strength of rock samples in the natural state is more sensitive to burial depth than that of saturated rock samples.

Table 2. Triaxial compression test results of dolomite in the natural state.

Depth (m)	Peak strength (MPa)				Cohesion (MPa)	Internal friction angle (°)
Depth (m)	σ3 = 5 MPa	σ3 = 10 MPa	σ3 = 15 MPa	σ3 = 20 MPa	Cohesion (MPa)	Internal friction angle (°)
770	152.92	212.55	290.13	303.31	16.49	55.40
867	132.56	182.86	253.39	338.26	7.08	59.98
1012	94.25	155.37	162.45	224.86	5.89	54.09
1120	84.38	167.33	235.41	175.59	3.67	59.16

Abbreviation: σ3, confining pressure.

Table 3. Triaxial compression test results of dolomite in the saturated state.

Depth (m)	Peak strength (MPa)				Cohesion (MPa)	Internal friction angle (°)
Depth (m)	σ3 = 5 MPa	σ3 = 10 MPa	σ3 = 15 MPa	σ3 = 20 MPa	Cohesion (MPa)	Internal friction angle (°)
770	67.90	117.39	180.38	237.38	1.128	57.07
867	68.51	89.61	113.96	192.03	1.141	52.62
1012	56.72	87.50	140.46	174.74	2.119	51.51
1120	93.38	92.54	173.58	150.37	3.333	54.82

4 DISCUSSION

At present, there are many kinds of in situ stress estimation and measurement methods. Based on where the data originate, these in situ methods can be classified into five categories: core-based methods, borehole-based methods, geological methods, geophysical methods, and underground-opening-based methods. Different methods have different application ranges and error ranges. The advantages, disadvantages, and application ranges of widely used in situ stress estimation and measurement methods are listed in Table 4. At the same time, there are obvious differences in the rock volume reflected by these methods. Different methods can reveal stress information at different scales. Therefore, the choice of in situ stress estimation and measurement methods should be adjusted in accordance with the specific requirements. Due to the complex geological environment of deep rock formations, the development trend of deep in situ stress testing technology mainly includes the following two aspects:

1.
Comprehensive measurement methods using multiple techniques are the main trend in future in situ stress measurement. This study explores the distribution characteristics of the current in situ stress field in northeast Yunnan Province by using multisource stress data, including in situ stress measurements, focal mechanism solutions, and borehole damage information, and comprehensively determines the in situ stress magnitude and direction in the mining area. Comprehensive measurement methods for determination are highly feasible in enhancing the reliability of the test results. However, the borehole breakouts method proposed in this study requires that the borehole show obvious borehole breakout phenomena and should not be influenced by the drilling mud, making its application relatively difficult.
2.
The development trend in in situ stress measurement is shifting from single-point testing toward three-dimensional field measurement, coupled with the integration of in situ measurement and numerical simulation. Currently, in situ stress measurements are conducted at a limited number of control points, and the measurement results only reflect the local stress at each measurement point. To conduct regional stress field analysis, based on the in situ test results and considering the topography, geological structure, and nonlinear characteristics of the rock mass, a three-dimensional stress field model is established for inversion analysis. Combined with the comparison and correction of in situ stress test results, in situ stress field characteristics close to the real state are obtained, thereby realizing the transformation from point measurement to field measurement.

Table 4. Comparisons of in situ stress estimation and measurement methods.

Serial number	Method category	Method	Stress information	Advantage	Disadvantage	Scope of application
1	Core-based method	Anelastic strain recovery (ASR)	Stress magnitude and direction	Using deep borehole to obtain stress information	Time dependence, with many influencing factors	Deep hole, soft rock
2		Differential strain curve analysis (DSCA)	Stress magnitude and direction	Economical and practical, not affected by core time	Many influencing factors	Deep hole, soft rock
3		Drilling-induced fracture in core (DIFC)	Stress magnitude and direction	The stress information in high-stress areas can be obtained	Phenomenon dependence, large error	High-stress areas, hard rock
4		Acoustic emission method (AE)	Stress magnitude and direction	Low cost, easy operation, high efficiency, and few limitations	Heavy workload, susceptibility to water, and significant data dispersion	Wide range of applications
5		Axial point load test	Stress magnitude and direction	The equipment is simple and easy to operate	Many influencing factors	Wide range of applications
6	Borehole-based method	Hydraulic fracturing (HF)	Stress magnitude and direction	Suitable for deep stress measurement without the need to obtain rock mass parameters, and simple operation	Large error, only the plane stress can be determined	Mainly used for intact brittle rocks
7		Overcoring method (OC)	Stress magnitude and direction	The theory is well developed, with minimal error, enabling three-dimensional stress measurement through a single borehole	Coring is difficult, requiring measurement of rock mass deformation, and the operation is complex	Wide range of applications
8		Borehole breakouts (BBO)	Stress magnitude and direction	Using deep borehole to obtain stress information is simple and fast	Phenomenon dependence and stress value error are large	Depth exceeds 1000 m
9		Drilling-induced fractures (DIF)	Stress magnitude and direction	It is simple and quick to obtain stress information by using deep holes	Phenomenon dependence and stress value error are large	Depth exceeds 1000 m
10		Borehole deformation	Stress magnitude and direction	Using deep borehole to obtain stress information	Phenomenon dependence and stress value error are large	Shallow hole
11	Geological method	Fault slip data	Stress direction, three-dimensional stress ratio	Obtaining large-volume rock mass stress information	The time of stress information is inaccurate	Tectonic stress field analysis
12	Geophysical method	Earthquake focal mechanisms	Stress direction, three-dimensional stress ratio	Able to effectively analyze deep in situ tress	Only the direction and relative magnitude of the regional tectonic stress induced by the earthquake source can be deduced	Tectonic stress field analysis
13	Underground-opening-based method	Jacking method	Stress magnitude and direction	Easy to operate, eliminating the necessity to calculate rock mass constitutive relations and mechanical parameters	Only one-dimensional stress measurement can be performed, and the measurement error is large	Underground space development
14	Underground-opening-based method	Surface relief methods	Stress magnitude and direction	Obtaining large-volume rock mass stress information	The testing process is cumbersome	Underground space development

5 CONCLUSIONS

In this study, hydraulic fracturing in situ stress tests and ultrasonic imaging logging were conducted, and in situ stress test data were collected near the mining area to comprehensively reveal the in situ stress field characteristics of the Maoping lead–zinc mining area and adjacent areas. The evolution of rock physical and mechanical properties with depth was analyzed so as to explore the influence of rock mechanical properties on the distributions of in situ stress fields in mining areas. From these investigations, the following conclusions can be drawn.

1.
The maximum and minimum horizontal lateral stress coefficients of the mining area stabilize at approximately 1.22 and 0.73, respectively. The principal stress relationship is σH > σV > σh, and the in situ stress magnitude is at a high stress level and in a strike–slip stress state. The in situ stress increases with burial depth, but the discreteness is significant.
2.
The current stress field in the mining area is dominated by NW-directed compression. Based on the two borehole breakout data, the average values of σH are calculated to be N58.44° W and N58.64° W. The average direction of in situ stress is determined to be N59.7° W based on induced tensile fractures from the borehole.
3.
Structural plane dip angles are dominated by gentler dip angles, steeper dip angles, and steep dip angles. The structural plane dip direction is predominantly NW–NWW. The distribution of the structural plane line density is characterized by high density in the shallow part and low density in the deep part.
4.
The UCS and elastic modulus of dolomite increase linearly with the burial depth, while the tensile strength remains approximately constant. The UCS and elastic modulus of rock are greater under higher in situ stress.
5.
The research results provide basic data for the mining design of the Maoping lead–zinc mining area. The measured data fill the gap in in situ stress data and offer important supplementary information for studying the distributions of in situ stress fields in deep mines in northeastern Yunnan.

AUTHOR CONTRIBUTIONS

Hui Wang: Conceptualization; funding acquisition; investigation; methodology; validation; writing—original draft. Bangtao Sun: Conceptualization; methodology; project administration; resources; supervision. Cong Cao: Writing—review and editing. Shibo Yu: Conceptualization; investigation; methodology; data analysis. He Wang: Supervision; validation. Ye Yuan: Investigation; validation. Hua Zhong: Validation.

ACKNOWLEDGMENTS

This work was financially supported by the National Key R&D Program of China (Grant no. 2022YFC2904100), the National Natural Science Foundation of China (Grant no. 5220409), and the Beijing Nova Program (Grant no. 20230484242).

CONFLICT OF INTEREST STATEMENT

The authors declare no conflict of interest.

Biography

Hui Wang is a lecturer at BGRIMM Technology Group, Beijing, China. She graduated from the University of Science and Technology Beijing with a major in civil engineering. Her main research interests include rock mechanics, rock fatigue mechanics, and the prevention and control of dynamic disasters. Dr. Wang has been involved in several major national engineering projects. She has published over 20 peer-reviewed papers, including articles in the International Journal of Rock Mechanics and Mining Sciences, Engineering Fracture Mechanics, and Rock and Soil Mechanics.