Numerical Modeling of CO<sub>2</sub> Storage in the Zharkent Depression Aquifers, South Kazakhstan
南カザフスタンのZharkent窪地帯水層におけるCO2貯留の数値モデリング (AI 翻訳)
Istekova S, Logvinenko A, Kairov D, Narimanov Y, Shamiyev N, Temirkhanova R, Slambek N
🤖 gxceed AI 要約
日本語
本論文は、カザフスタン南部のZharkent窪地におけるCO2貯留の可能性を評価する。地震探査と坑井データを用いて3次元地質モデルと流体力学モデルを構築し、ジュラ紀帯水層が貯留に適することを示した。長期注入シミュレーションにより、経済性評価を含む最適貯留戦略を提案し、2126年までのCO2貯留ポテンシャルを定量化した。
English
This paper evaluates the CO2 storage potential of the Zharkent Depression in Kazakhstan, integrating seismic and well data into 3D geological and hydrodynamic models. It identifies Jurassic aquifers as favorable and simulates injection dynamics with economic assessment, quantifying storage potential through 2126.
Unofficial AI-generated summary based on the public title and abstract. Not an official translation.
📝 gxceed 編集解説 — Why this matters
日本のGX文脈において
日本においてもCCUSはカーボンニュートラル達成の重要なオプションであり、本論文のような海外貯留サイトの評価手法は、日本の企業が海外CCSプロジェクトに参加する際の参考となる。特に、地質データと経済性を統合したアプローチは実務上有用である。
In the global GX context
Globally, CCUS is a key mitigation technology, and this study provides a comprehensive workflow for evaluating storage sites from geology to economics. It demonstrates how to integrate seismic, well, and hydrodynamic data to assess long-term storage capacity, relevant for ISSB/TCFD disclosure on climate transition plans.
👥 読者別の含意
🔬研究者:This paper presents a full pipeline from geological modeling to economic assessment for CO2 storage, useful for researchers in CCUS geoscience.
🏢実務担当者:The methodology and findings can guide corporate evaluation of CCS feasibility in similar sedimentary basins, aiding in project development.
🏛政策担当者:Highlights the potential of regional storage resources and the importance of integrated assessment for national CCS strategies.
📄 Abstract（原文）
This paper presents the results of research evaluating the potential of the Zharkent Depression in Southern Kazakhstan as a promising geological structure for identifying natural reservoirs within aquifer formations for long-term underground CO2 storage. Based on seismic and well data integrated with modern geographic information sys-tems (GIS), digital surface models of reflecting horizons correlated with structur-al-stratigraphic complexes were constructed. Structural, lithological, and petrophysical modeling was performed, providing three-dimensional distributions of lithology and porosity, as well as reservoir saturation forecasts. The geological reservoir model was developed using geostatistical analysis principles. The three-dimensional geo-hydrodynamic model is based on numerical methods for estimating reservoir hydrodynamic parameters. The injection dynamics and under-ground gas storage models, including an economic efficiency assessment, were calcu-lated for a long-term period. It was established that the Jurassic aquifers, characterized by thick sandstone sequences with enhanced reservoir properties (porosity and permeability), represent the most favorable environment for carbon dioxide injection and storage. Simulation of the in-jection and storage processes yielded predictive saturation cubes and quantitative characterization of CO2 volume and distribution within the trap under specified injec-tion conditions. The potential volume of injected gas was calculated, and an optimal CO2 storage strategy in the aquifer was determined through the year 2126. The findings indicate that the storage reservoirs in the Zharkent Depression possess a CO2 seques-tration potential comparable to existing global large-scale carbon capture and storage projects.
🔗 Provenance — このレコードを発見したソース
- Research Square https://doi.org/10.20944/preprints202606.0809.v1first seen 2026-06-20 04:52:49 · last seen 2026-06-21 04:45:02
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