成果報告書詳細
管理番号20120000000141
タイトル*平成23年度中間年報 革新的ゼロエミッション石炭ガス化発電プロジェクト発電からCO2貯留までのトータルシステムのフィジビリティー・スタディー CO2の貯留システムの概念設計と貯留ポテンシャル評価(H20~H24)
公開日2012/6/9
報告書年度2011 - 2011
委託先名公益財団法人地球環境産業技術研究機構 応用地質株式会社
プロジェクト番号P08020
部署名環境部
和文要約1. 研究開発の内容及び成果等
(1) 貯留層評価手法の構築
e 貯留層経済性評価ツールの作成(RITE)
想定地点の貯留層調査結果より得られた、深度、圧入レート、浸透率等の貯留層データをグリッド化し、貯留層データベースの更新を行い貯留層データの精度向上を図った。また、貯留設備概念設計の費用算定結果からコストデータ更新の検討を行った。
(2) 国内貯留層データの収集と貯留層GISデータベース化(応用地質)
追加サイト(D地点)における貯留概念設計等の基礎情報とするため、昨年度までに収集したD地点の地質情報や地理情報に関する既往調査データを検討・整理し、GISデータを更新した。
英文要約Research Institute of Innovative Technology for the Earth (RITE)
OYO Corporation
RITE and OYO Corporation investigated “Design of CO2 geologic storage system and evaluation of storage potential” for feasibility study on “Innovative Zero-emission Coal Gasification Power Generation”. Conclusive remarks of 2011 works are summarized as follows:

1.After surveying information on reservoirs in Japan and conceptual design results of CO2 storage facilities, the reservoir database, the cost database and the economic evaluation tool of CO2 storage were updated.
2.In order to examine the CO2 storage conceptual design in the site D, the previous geological survey data in the site D was re-arranged, and the GIS database was updated.
The main updated contents of the GIS database were the stratum boundary depth of the reservoir and the seal layer, large fault, water depth, etc. in the creation range of a three-dimensional geological model (about 30 km around).
3.The planned storage 4 areas for large scale CCS were selected from the site D. The following points were mainly considered for the selection:
・ The amount of large-scale CO2 storage was assumed to be 200 million tons in total. The annual amount of CO2 storage was 10 million tons in 20 years.
Such amounts of CO2 can be store.
・ An area with less large-scale faulting.
・ Near drilling (higher reliability geology information).
The three-dimensional geological model include the 4areas was built, and the formation characteristics such as the continuity and rock properties of the targeted reservoirs and seals were re-evaluated.
4.The total of CO2 storage capacity of the 4 areas was 380 million tons of CO2. This value was calculated by following equation:GCO2=A×h×φ×ρ×Sg×Sf
Where A is horizontal area of aquifer, h is effective thickness of aquifer andφ is porosity. Sg is gas saturation of supercritical CO2 in pore space, which we assumed to be 0.5. ρ is CO2 density at storage depth. Sf is storage factor that represents ratio of CO2 plume volume to total pore volume, which we assumed to be 0.25.
The number and arrangement of injection wells were examined by the simulation using TOUGH2/ECO2N. As a result of examining arrangement of injection wells, the predetermined quantities of CO2 can be stored in planed areas with 10 injection wells.
5.Based on the results of the CO2 simulations (injection rates, number of injection wells, etc.) and the previous studies, a conceptual design of the CO2 storage facilities for the additional CO2 injection site and work schedules for the construction of the facilities were developed, and the CO2 storage costs such as the construction and monitoring costs were estimated.
In addition, a conceptual design of the CO2 storage facilities and work schedules for the construction of the facilities for a larger-scale CO2 storage also were developed, and the construction costs were estimated.
6.A comparison of the estimated costs between the commercial- and larger-scale storages in the above-mentioned additional site indicates that the latter case is more cost-effective in terms of cost per ton of CO2.
・ A feasibility study on the CO2 export from Japan were targeted on the two projects in Australia and Southeast Asia, and the information necessary for estimating the transport costs were gathered and analyzed.
・ An overall workflow for the CO2 storage system were reviewed, and some adjustments were made in order to keep consistency among work plans and studies.
・ Comparisons of the assumptions for the cost estimates between the ZEP’s (2011) study and our results indicate that changes in parameter values for some assumptions result in cost reduction.
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