Slurry infiltration characteristics of coral reef limestone based on infiltration column tests and CT scanning

Abstract

Reef limestone is buried in the continental shelf and marine environment. Understanding the mechanisms governing filter cake formation in coral reef limestone strata is essential for various engineering activities in coastal areas, including slurry pressure balanced (SPB) shield tunneling, which are currently not well understood. This study systematically investigates the slurry infiltration characteristics of different coral reef limestone types with inherent anisotropy, identified by growth line orientations, through a series of micro-infiltration column tests. Multiple slurry concentrations and pressures were used to analyze their effects on slurry infiltration dynamics and filter cake formation. Pre- and post-infiltration CT scanning was conducted to examine skeletal morphology and reconstruct the pore network structure of coral reef limestone samples. The results show that while increased slurry concentrations and pressures generally improve filter cake formation, excessive pressure can compromise filter cake integrity. By employing Dijkstra’s algorithm in a pore network model, the study identified primary seepage pathways, highlighting the significant role of near-vertical throat clusters in the infiltration process. A comprehensive analysis of pore structure and connectivity indices before and after infiltration revealed that the orientation of growth lines in coral reef limestone is the primary factor influencing macroscopic slurry infiltration behavior. These findings offer valuable insights for the design and execution of tunneling projects through coral reef limestone formations, especially in coastal regions.

Keywords

Coral reef limestone / Slurry infiltration / CT scanning / Pore network model / Dominant seepage path

Acknowledgments

The technical support from Haozhen Yuan and Jun Xu in pore structure analysis is highly appreciated.

References

[1] Gu GS, Zhang ZX, Huang X, Li Y, Lei QH.A finite element-based dynamic simulation method for modeling shield-ground interactions: 3D numerical simulations with comparison to physical experiments. Comput Geotech 2024;169:106262.

[2] Fritz P. Additives for slurry shields in highly permeable ground. Rock Mech Rock Eng 2007; 40(1):81-95.

[3] Jebelli J, Meguid MA, Sedghinejad MK. Excavation failure during micro-tunneling in fine sands: a case study. Tunn Undergr Space Technol 2010; 25 (6):811-8.

[4] Yuan HZ, Zhang ZX, Huang X, Li Y. Comparing, slurry infiltration characteristics between calcareous and silica sands based on slurry infiltration column tests and CT scanning. Tunn Undergr Space Technol 2024;152:105919.

[5] Wang JP, Huang X, Xu J, Zhang ZX, Wang SF, Li Y. Network analysis of pore structure of coral reef limestone and its implications for seepage flow. Eng Geol 2023;318:107103.

[6] Ma LJ, Deng JJ, Wang MY, Wang JP, Fang B, Wu JW. Effect of diagenetic variation on the static and dynamic mechanical behavior of coral reef limestone. Int J Min Sci Technol 2024; 34(7):893-908.

[7] Liu HF, Zhu CQ, Zheng K, Ma CH, Yi MX. Crack initiation and damage evolution of micritized framework reef limestone in the South China Sea. Rock Mech Rock Eng 2021; 54(11):5591-601.

[8] Meng QS, Wu K, Zhou HR, Qin QL, Wang C. Mesoscopic damage evolution of coral reef limestone based on real-time CT scanning. Eng Geol 2022;307:106781.

[9] Bai JH, Huang X, Li Y, Lei QH. Investigating slurry infiltration in a coral reef limestone based on X-ray computed tomography and CFD-DEM numerical simulation. Powder Technol 2024;443:119972.

[10] Min FL, Du JR, Zhang N, Chen XG, Lv HJ, Liu LC, et al. Experimental study on property change of slurry and filter cake of slurry shield under seawater intrusion. Tunn Undergr Space Technol 2019;88:290-9.

[11] Lu Z, Zhou WH, Yin ZY. Effect of viscosity on slurry infiltration in granular media. Int J Geomech 2022; 22(9):04022138.

[12] Xu T, Zhou W-H, Bezuijen A, Qin S. Effects of sand and slurry characteristics on pressure infiltration of bentonite slurry into sand. Géotechnique 2024; 74 (9):935-46.

[13] Talmon AM, Mastbergen DR, Huisman M. Invasion of pressurized clay suspensions into granular soil. J Por Media 2013; 16(4):351-65.

[14] Zhang ZX, Yin T, Huang X, Dias D. Slurry filtration process and filter cake formation during shield tunnelling: Insight from coupled CFD-DEM simulations of slurry filtration column test. Tunn Undergr Space Technol 2019;87:64-77.

[15] Chen F, Xiong H, Yin ZY, Chen XS. Impermeable and mechanical stability of filter cake under different infiltration conditions via CFD-DEM. Acta Geotech 2023; 18(8):4115-40.

[16] Cheng Z, Wang JF. A particle-tracking method for experimental investigation of kinematics of sand particles under triaxial compression. Powder Technol 2018;328:436-51.

[17] Qin XJ, Cai JC, Wang G. Pore-scale modeling of pore structure properties and wettability effect on permeability of low-rank coal. Int J Min Sci Technol 2023; 33(5):573-84.

[18] Cnudde V, Boone MN. High-resolution X-ray computed tomography in geosciences: a review of the current technology and applications. Earth Sci Rev 2013;123:1-17.

[19] Qin XJ, Xia YX, Qiao JC, Chen JH, Zeng JH, Cai JC. Modeling of multiphase flow in low permeability porous media: effect of wettability and pore structure properties. J Rock Mech Geotech Eng 2024; 16(4):1127-39.

[20] Luo Y, Zhang MC, Gong HL, Jing W, Li XP. Microscopic pore structural characteristics and grout diffusion law of coral reef limestone. Mar Geophys Res 2023; 44(2):14.

[21] Bai JH, Huang X, Lei QH. Characterizing the permeability anisot ropy of coral reef limestone based on CT scanning and CFD modeling. Rock Mech Rock Eng 2025.

[22] Min FL, Song HB, Zhang N. Experimental study on fluid properties of slurry and its influence on slurry infiltration in sand stratum. Appl Clay Sci 2018;161:64-9.

[23] Xu T, Bezuijen A. Bentonite slurry infiltration into sand: Filter cake formation under various conditions. Géotechnique 2019; 69(12):1095-106.

[24] Scientific TF, Thermo Scientific Avizo Software User’s Guide. 2022.

[25] Blunt MJ. Flow in porous media: Pore-network models and multiphase flow. Curr Opin Colloid Interface Sci 2001; 6(3):197-207.

[26] Raoof A, Hassanizadeh SM. A new method for generating pore-network models of porous media. Transp Porous Medium 2010; 81(3):391-407.

[27] Rabbani A, Ayatollahi S, Kharrat R, Dashti N.Estimation of 3-D pore network coordination number of rocks from watershed segmentation of a single 2-D image. Adv Water Resour 2016;94:264-77.

[28] Kwok P. A thinning algorithm by contour generation. Commun ACM 1988; 31 (11):1314-24.

[29] Silin D, Patzek T. Pore space morphology analysis using maximal inscribed spheres. Phys A Stat Mech Appl 2006; 371(2):336-60.

[30] Youssef S, Rosenberg E, Gland N, Kenter JAM, Skalinski M, Vizika O.High resolution CT and pore-network models to assess petrophysical properties of homogeneous and heterogeneous carbonates. SPE/EAGE Reservoir Characterization and Simulation Conference. Abu Dhabi: SPE&EAGE; 2007.

[31] Dijkstra EW. A note on two problems in connexion with graphs. Numer Math 1959; 1(1):269-71.

[32] Tritton DJ. Physical fluid dynamics. New York: Van Nostrand Reinhold Company; 1977.

[33] Kornilov AS, Safonov IV. An overview of watershed algorithm implementations in open source libraries. J Imag 2018; 4(10):123.

[34] Bieniek A, Moga A. An efficient watershed algorithm based on connected components. Pattern Recogn 2000; 33(6):907-16.

[35] Wen T, Cheong KH. The fractal dimension of complex networks: A review. Inf Fusion 2021;73:87-102.