Experimental study on the influence of heavy mud loss during workover on re-fracturing of high-pressure gas wells

Abstract

During workover operations in high-pressure gas wells, heavy mud losses may occur, reducing gas production. Refracturing is an effective means to restore production. The influence of heavy mud loss on refracturing is still unclear. In this paper, split core is designed to simulate the fractures of the initial transformation, transparent sand-filled pipe is designed to simulate the sand filled fractures, and the experiment of heavy mud leakage in artificial fractures under different conditions is carried out by using the displacement device, combined with CT scanning and pressure monitoring means. The influence of heavy mud loss on permeability of artificial fracture, repeated reconstruction construction pressure and flow channel configuration in artificial fracture is analyzed. The results show that workover heavy mud (WHM) loss has the greatest permeability damage to the proppant fracture packed with large particle size, up to 97%, and the fracture permeability damage of 40/70 mesh ceramsite packing is only 0.3%-0.7%. Slit core permeability damage is the least, and the decrease range is 10%-20%. The damage of matrix core permeability measured by gas is no less than 60%. Before and after the loss of WHM, the injection pressure increases significantly, up to 80 times. Combined with the CT scan results, it is found that after WHM loss, the nitrogen blowout and refracturing incompletely remove the pollution, and there is a “pollution cage” in the fracture, which is the main reason for the high construction pressure of refracturing and low production after refracturing. The research results provide theoretical basics for the refracturing of WHM loss wells.

Keywords

High-pressure gas well / Workover / Refracturing / Heavy mud leakage / Loss medium

CRediT authorship contribution statement

Yuxuan Liu: Funding acquisition, Writing-original draft, Writing-review & editing. Minghao Jiang: Writing-review & editing, Writing-original draft. Jianchun Guo: Funding acquisition, Methodology. Xinggui Yang: Methodology, Formal analysis, Validation. Jiamin Wu: Methodology, Formal analysis. Liansong Wu: Writing-Review & Editing. Xiaopeng Chen: Data curation. Zhiming Wen: Data curation. Chuanyun Zhou: Data curation.

Availability of data and materials

Data will be made availability on request.

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

This paper was supported by the National Natural Science Foundation Enterprise Innovation and Development Joint fund of China (No.U23B6004).

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