Experimental evaluation method of density suitability between bridging lost circulation materials and drilling fluid

Abstract

Ultra-deep geological conditions are complex, often leading to leakage issues. As the depth increases during ultra-deep bridging lost-circulation operations, the varying settling velocities of different types of lost circulation materials (LCMs) lead to gravitational differentiation. This causes stratification of the LCMs, forming an unevenly dispersed system and reduced plugging efficacy. An experimental methodology is described for assessing the density suitability between LCMs and drilling fluid, which calculates the density suitability factor (DSF) by measuring the density of the plugging slurry at various locations after a designated resting period, ultimately evaluating its density suitability based on the DSF. Experimental results indicate that LCMs with lower densities demonstrate superior density suitability compared to those with higher densities. Smaller particle sizes (10-40 mesh) show better density suitability than larger ones (2-6 mesh). Fracture-plugging experiments validated this method, the plugging slurry composed of a good density suitability material, such as walnut shells, exhibited no notable gravitational differentiation after 2 h, achieving a maximum plugging pressure of 16.4 MPa with 88 mL of total volume loss. In contrast, the slurry formed with poorly density suitability materials, such as calcite, showed significant gravitational differentiation after 2 h, achieving only 9.6 MPa in maximum plugging pressure and a total volume loss of 96 mL. These findings highlight that LCMs with superior density suitability enhance plugging efficiency, highlighting the critical role of density suitability testing and the optimization of plugging formulations to improve the success of plugging operations.

Keywords

Ultra-deep reservoir / Bridging lost circulation materials / Drilling fluid / Density suitability

CRediT authorship contribution statement

Yili Kang: Validation, Supervision, Methodology, Formal analysis. Ketao Hao: Writing-original draft, Software, Investigation, Data curation. Chengyuan Xu: Resources, Project administration, Investigation, Funding acquisition, Formal analysis. Kun Guo: Supervision, Data curation. Jie Zhou: Investigation. Ruiheng Wang: Validation. Yao Xiao: Validation. Yunsong Xie: Software.

Declaration of competing interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Acknowledgements

The authors gratefully acknowledge the financial support from the National Natural Science Foundation of China (Grant Nos. 52274009, 51604236), the Sichuan Province Youth Science and technology innovation team project (No. 2021JDTD0017), and the Sichuan Province Science and Technology Project (Grant No. 2018JY0436).

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