Real-time monitoring and analysis of hydraulic fracturing in surface well using microseismic technology: Case insights and methodological advances

Yanan Qian; Ting Liu; Cheng Zhai; Hongda Wen; Yuebing Zhang; Menghao Zheng; Hexiang Xu; Dongyong Xing; Xinke Gan

doi:10.1016/j.ijmst.2025.02.009

Int J Min Sci Technol ›› 2025, Vol. 35 ›› Issue (4) : 619 -638. DOI: 10.1016/j.ijmst.2025.02.009

Real-time monitoring and analysis of hydraulic fracturing in surface well using microseismic technology: Case insights and methodological advances

Yanan Qian ^a^,^b^,^c^,^d
, Ting Liu ^a^,^b^,^c^,^d^,^*
, Cheng Zhai ^a^,^b^,^c^,^d
, Hongda Wen ^a^,^b^,^c^,^d
, Yuebing Zhang ^e
, Menghao Zheng ^f
, Hexiang Xu ^a^,^b^,^c^,^d
, Dongyong Xing ^g
, Xinke Gan ^g

Author information +

History +

PDF (24377KB)

Abstract

Through a case analysis, this study examines the spatiotemporal evolution of microseismic (MS) events, energy characteristics, volumetric features, and fracture network development in surface well hydraulic fracturing. A total of 349 MS events were analyzed across different fracturing sections, revealing significant heterogeneity in fracture propagation. Energy scanning results showed that cumulative energy values ranged from 240 to 1060 J across the sections, indicating notable differences. Stimulated reservoir volume (SRV) analysis demonstrated well-developed fracture networks in certain sections, with a total SRV exceeding 1540000 m³. The hydraulic fracture network analysis revealed that during the mid-fracturing stage, the density and spatial extent of MS events significantly increased, indicating rapid fracture propagation and the formation of complex networks. In the later stage, the number of secondary fractures near fracture edges decreased, and the fracture network stabilized. By comparing the branching index, fracture length, width, height, and SRV values across different fracturing sections, Sections No. 1 and No. 8 showed the best performance, with high MS event densities, extensive fracture networks, and significant energy release. However, Sections No. 4 and No. 5 exhibited sparse MS activity and poor fracture connectivity, indicating suboptimal stimulation effectiveness.

Keywords

Hydraulic fracturing / Microseismic / Source location / Energy scanning / Fracture network

Cite this article

Download citation ▾

Yanan Qian, Ting Liu, Cheng Zhai, Hongda Wen, Yuebing Zhang, Menghao Zheng, Hexiang Xu, Dongyong Xing, Xinke Gan. Real-time monitoring and analysis of hydraulic fracturing in surface well using microseismic technology: Case insights and methodological advances. Int J Min Sci Technol, 2025, 35(4): 619-638 DOI:10.1016/j.ijmst.2025.02.009

登录浏览全文

4963

注册一个新账户忘记密码

Acknowledgements

This work was supported by Yunlong Lake Laboratory of Deep Underground Science and Engineering Project (No. 104024008), the National Natural Science Foundation of China (Nos. 52274241 and 52474261), and the Natural Science Foundation of Jiangsu Province (No. BK20240207).

References

Publishing order | Descend order by publishing year | Descend order by cited within

[1]	Yang ZQ, Liu C, Zhu HZ, Xie FX, Dou LM, Chen JH. Mechanism of rock burst caused by fracture of key strata during irregular working face mining and its prevention methods. Int J Min Sci Technol 2019; 29(6):889-97.

[2]	Huang BX, Wang YZ, Cao SG. Cavability control by hydraulic fracturing for top coal caving in hard thick coal seams. Int J Rock Mech Min Sci 2015;74:45-57.

[3]	Ge ZL, Li SH, Zhou Z, Lu YY, Xia BW, Tang JR. Modeling and experiment on permeability of coal with hydraulic fracturing by stimulated reservoir volume. Rock Mech Rock Eng 2019; 52(8):2605-15.

[4]	Wang T, Hu WR, Elsworth D, Zhou W, Zhou WB, Zhao XB, Zhao LZ. The effect of natural fractures on hydraulic fracturing propagation in coal seams. J Petrol Sci Eng 2017;150:180-90.

[5]	Lyu SF, Wang SW, Chen XJ, Wang SF, Wang T, Shi XH, Dong QX, Li JY. Natural fractures in soft coal seams and their effect on hydraulic fracture propagation: A field study. J Petrol Sci Eng 2020;192:107255.

[6]	Huang LS, Li B, Wang B, Zhang JX. Effects of coal bedding dip angle on hydraulic fracturing crack propagation. Geomech Geophys Geo Energy Geo Resour 2023; 9(1):30.

[7]	Xia BW, Zhou YM, Zhang XG, Zhou L, Ma ZK. Physical and numerical investigations of target stratum selection for ground hydraulic fracturing of multiple hard roofs. Int J Min Sci Technol 2024; 34(5):699-712.

[8]	Chen CJ, Wei JP, Zhang TG, Zhang HD, Liu Y. Effect of abrasive volume fraction on energy utilization in suspension abrasive water jets based on VOF-DEM method. Powder Technol 2025;449:120427.

[9]	Ma K, Sun XY, Tang CA, Yuan FZ, Wang SJ, Chen T. Floor water inrush analysis based on mechanical failure characters and microseismic monitoring. Tunn Undergr Space Technol 2021;108:103698.

[10]	Mou PW, Pan JN, Wang K, Wei J, Yang YH, Wang XL. Influences of hydraulic fracturing on microfractures of high-rank coal under different in situ stress conditions. Fuel 2021;287:119566.

[11]	Liang YP, Cheng YH, Zou QL, Wang WD, Ma YK, Li QG. Response characteristics of coal subjected to hydraulic fracturing: An evaluation based on real-time monitoring of borehole strain and acoustic emission. J Nat Gas Sci Eng 2017;38:402-11.

[12]	Lu YX, Meng ZP, Su XF, Yu YN. Experimental study of dynamic permeability changes in coals of various ranks during hydraulic fracturing. Nat Resour Res 2022; 31(6):3253-72.

[13]	Wang S, Li HM, Li DY. Numerical simulation of hydraulic fracture propagation in coal seams with discontinuous natural fracture networks. Processes 2018; 6 (8):113.

[14]	Li R, Wang SW, Li GF, Wang JC. Influences of coal seam heterogeneity on hydraulic fracture geometry: An in situ observation perspective. Rock Mech Rock Eng 2022; 55(7):4517-27.

[15]	Liu YL, Tang DZ, Xu H, Hou W, Yan X. Analysis of hydraulic fracture behavior and well pattern optimization in anisotropic coal reservoirs. Energy Explor Exploit 2021; 39(1):299-317.

[16]	Li QG, Qian YN, Hu QT, Jiang ZZ, Xu YC, Shang XY, Ling FP, Liu R, Li WX. Acoustic emission response mechanism of hydraulic fracturing in different coal and rock: A laboratory study. Rock Mech Rock Eng 2022; 55(8):4657-72.

[17]	Tan P, Jin Y, Yuan L, Xiong ZY, Hou B, Chen M, Wan LM. Understanding hydraulic fracture propagation behavior in tight sandstone-coal interbedded formations: An experimental investigation. Petrol Sci 2019; 16(1):148-60.

[18]	Zhao HF, Liu CS, Xiong YG, Zhen HB, Li XJ. Experimental research on hydraulic fracture propagation in group of thin coal seams. J Nat Gas Sci Eng 2022;103:104614.

[19]	Liu P, Ju Y, Feng Z, Mao LT. Characterization of hydraulic crack initiation of coal seams under the coupling effects of geostress difference and complexity of pre-existing natural fractures. Geomech Geophys Geo Energy Geo Resour 2021; 7(4):91.

[20]	Xie AY, Li BQ. Transfer learning framework for multi-scale crack type classification with sparse microseismic networks. Int J Min Sci Technol 2024; 34(2):167-78.

[21]	Dou LM, Cai W, Cao AY, Guo WH. Comprehensive early warning of rock burst utilizing microseismic multi-parameter indices. Int J Min Sci Technol 2018; 28 (5):767-74.

[22]	Lu ZH, Jia YZ, Cheng LJ, Pan ZJ, Xu LJ, He P, Guo XZ, Ouyang LM. Microseismic monitoring of hydraulic fracture propagation and seismic risks in shale reservoir with a steep dip angle. Nat Resour Res 2022; 31(5):2973-93.

[23]	Shakiba M, de Araujo Cavalcante Filho JS, Sepehrnoori K. Using embedded discrete fracture model (EDFM) in numerical simulation of complex hydraulic fracture networks calibrated by microseismic monitoring data. J Nat Gas Sci Eng 2018;55:495-507.

[24]	Shao YY, Huang XR, Xing Y. An integrated study on the sensitivity and uncertainty associated with the evaluation of stimulated reservoir volume (SRV). J Petrol Sci Eng 2017;159:903-14.

[25]	Fischer T, Hainzl S, Eisner L, Shapiro SA, Le Calvez J. Microseismic signatures of hydraulic fracture growth in sediment formations: Observations and modeling. J Geophys Res Solid Earth 2008; 113(B2):B02307.

[26]	Ma YY, Eaton DW, Wang CY, Aklilu A. Characterizing hydraulic fracture growth using distributed acoustic sensing-recorded microseismic reflections. Geophysics 2023; 88(6):WC47-57.

[27]	Zhu QJ, Feng Y, Cai M, Liu JH, Wang HH. Interpretation of the extent of hydraulic fracturing for rockburst prevention using microseismic monitoring data. J Nat Gas Sci Eng 2017;38:107-19.

[28]	Qian YN, Li QG, Liang YP, Hu QT, Li WX, Li J, Yu CJ, Liu RH, Peng SY. Evaluation of hydraulic fracturing in coal seam using ground microseismic monitoring and source location. Rock Mech Rock Eng 2024; 57(1):679-94.

[29]	Qian YN, Fiorucci M, Marmoni GM, Li QG, Hussain Y, Grechi G, Martino S. Impact of environmental stressors on jointed rock cliffs by acoustic emission sensing: Preliminary findings from the Acuto field laboratory (central Italy). Rock Mech Rock Eng 2024;58:1549-68.

[30]	Liu C, Li SG, Cheng C, Cheng XY. Identification methods for anomalous stress region in coal roadways based on microseismic information and numerical simulation. Int J Min Sci Technol 2017; 27(3):525-30.

[31]	Dong LJ, Shu HM, Tang Z, Yan XH. Microseismic event waveform classification using CNN-based transfer learning models. Int J Min Sci Technol 2023; 33 (10):1203-16.

[32]	Tagne Fute E, Nyabeye Pangop DK, Tonye E. A new hybrid localization approach in wireless sensor networks based on particle swarm optimization and tabu search. Appl Intell 2022; 53(7):7546-61.

[33]	Pan DD, Li SC, Xu ZH, Zhang YC, Lin P, Li HY. A deterministic-stochastic identification and modelling method of discrete fracture networks using laser scanning: Development and case study. Eng Geol 2019;262:105310.

[34]	Qin QL, Zhou K, Wei B, Du QJ, Liu YG, Li X, Hou J. Experimental and simulation study on deep reservoir fracturing technology: A review and future perspectives. Geoenergy Sci Eng 2024;242:213209.