GLDA chelation-driven mineral dissolution for enhanced porosity and permeability in coalbed methane reservoirs: An experimental study

Abstract

Conventional acidification for coalbed methane (CBM) reservoir stimulation is challenged by equipment corrosion, secondary reservoir damage, and environmental pollution. To address these limitations, this study proposes and rigorously evaluates an environmentally friendly alternative to reservoir acidification using low-corrosion, biodegradable chelating agents. Laboratory experiments included static dissolution tests on coal fines, analysis of variations in soluble metal ions, core flooding under simulated reservoir conditions, and porosity measurements. The results indicate that GLDA (L-glutamic acid, N,N-diacetic acid) at 10 wt% and pH = 2 achieved a dissolution rate of 6.55%, with Ca and Fe concentrations in the filtrate reaching 19.66 mg/L and 22.2 mg/L, respectively. Dynamic core flooding tests showed that 10 wt% GLDA (pH = 2) at an injection rate of 0.5 mL/min achieved the maximum permeability enhancement, increasing by 42.08% from 9.03 × 10⁻² mD to 1.283 × 10⁻¹ mD, while simultaneously increasing coal porosity by 13.87%. The effectiveness of GLDA is mainly attributed to the formation of stable chelates with Ca and Fe that remain in the aqueous phase, thereby avoiding secondary reservoir damage associated with precipitation in conventional acid systems. The findings of this study may provide an effective reference guide for CBM acidification.

Keywords

Coalbed methane / Eco-friendly acidizing / GLDA chelating agent / Mineral dissolution / Permeability enhancement

CRediT authorship contribution statement

Zexin Chen: Writing – review & editing, Writing – original draft, Visualization, Methodology, Investigation, Formal analysis, Data curation, Conceptualization. Shuya Chen: Writing – review & editing, Validation, Supervision, Methodology, Conceptualization. Shuhao Tan: Visualization, Methodology, Data curation. Chuanjie Deng: Visualization, Data curation. Jihua Cai: Writing – review & editing, Supervision, Resources, Project administration, Funding acquisition, Conceptualization. Xianyu Yang: Writing – review & editing, Supervision, Methodology.

Data availability

Data will be made available on request.

Funding

The publishing of this paper is financially supported by the National Natural Science Foundation of China (Grant No. 42572289, Grant No. 42472375).

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.

Acknowledgments

The publishing of this paper is financially supported by the National Natural Science Foundation of China (No. 42572289, No. 42472375).

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