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Chapter 5: Underground geological storage 251 table 5.6 Representative selection of risk assessment models and efforts. Project title Description and status Weyburn/ECOMatters New model, CQUESTRA, developed to enable probabilistic risk assessment. A simple box model is used with explicit representation of transport between boxes caused by failure of wells. Weyburn/Monitor Scientific Scenario-based modelling that uses an industry standard reservoir simulation tool (Eclipse3000) based on a realistic model of known reservoir conditions. Initial treatment of wells involves assigning a uniform permeability. NGCAS/ECL technology Probabilistic risk assessment using fault tree and FEP (features, events and processes) database. Initial study focused on the Forties oil and gas field located offshore in the North Sea. Concluded that flow through caprock transport by advection in formation waters not important, work on assessing leakage due to well failures ongoing. SAMARCADS (safety aspects of CO2 storage) Methods and tools for HSE risk assessment applied to two storage systems an onshore gas storage facility and an offshore formation. RITE Scenario-based analysis of leakage risks in a large offshore formation. Will assess scenarios involving rapid release through faults activated by seismic events. Battelle Probabilistic risk assessment of an onshore formation storage site that is intended to represent the Mountaineer site. GEODISC Completed a quantitative risk assessment for four sites in Australia: the Petrel Sub-basin; the Dongra depleted oil and gas field; the offshore Gippsland Basin; and, offshore Barrow Island. Also produced a risk assessment report that addressed the socio-political needs of stakeholders. UK-DTI Probabilistic risk assessment of failures in surface facilities that uses models and operational data. Assessment of risk of release from geological storage that uses an expert-based Delphi process. models are designed to allow explicit treatment of uncertainty in input parameters (Saripalli et al., 2003; Stenhouse et al., 2005; Wildenborg et al., 2005a). formal quantification of expert judgements (Morgan and Henrion, 1999). In some cases, probabilistic risk assessment may require that the models be simplified because of limitations on available computing resources. Our understanding of abandoned-well behaviour over long time scales is at present relatively poor. Several groups are now collecting data on the performance of well construction materials in high-CO2 environments and building wellbore simulation models that will couple geomechanics, geochemistry and fluid transport (Scherer et al., 2005; Wilson and Monea, 2005). The combination of better models and new data should enable the integration of physically based predictive models of wellbore performance into larger performance-assessment models, enabling more systematic assessment of leakage from wells. Studies of natural and engineered analogues provide a strong basis for understanding and quantifying the health, safety and environmental risks that arise from CO2 that seeps from the shallow subsurface to the atmosphere. Natural analogues are of less utility in assessing the likelihood of various processes that transport CO2 from the storage reservoir to the near-surface environment. This is because the geological character of such analogues (e.g., CO2 transport and seepage in highly fractured zones shaped by volcanism) will typically be very different from sites chosen for geological storage. Engineered analogues such as natural gas storage and CO2-EOR can provide a basis for deriving quantitative probabilistic models of well performance. The parameter values (e.g., permeability of a caprock) and the structure of the performance assessment models (e.g., the processes included or excluded) will both be, in general, uncertain. Risk analysis may or may not treat this uncertainty explicitly. When risks are assessed deterministically, fixed parameter values are chosen to represent the (often unknown) probability distributions. Often the parameter values are selected ‘conservatively’; that is, they are selected so that risks are overestimated, although in practice such selections are problematic because the relationship between the parameter value and the risk may itself be uncertain. Results from actual risk and assessment for CO2 storage are provided in 5.7.3. Wherever possible, it is preferable to treat uncertainty explicitly. In probabilistic risk assessments, explicit probability distributions are used for some (or all) parameters. Methods such as Monte Carlo analysis are then used to produce probability distributions for various risks. The required probability distributions may be derived directly from data or may involve Risk management entails the application of a structured process to identify and quantify the risks associated with a given process, to evaluate these, taking into account stakeholder input and context, to modify the process to remove excess risks and to identify and implement appropriate monitoring and intervention strategies to manage the remaining risks. 5.7.6 Risk management For geological storage, effective risk mitigation consists of four interrelated activities: • Careful site selection, including performance and riskPDF Image | CARBON DIOXIDE CAPTURE AND STORAGE
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